Interspike Interval Research Articles

A Role for STOML3 in Olfactory Sensory Transduction.

Stomatin-like protein-3 (STOML3) is an integral membrane protein expressed in the cilia of olfactory sensory neurons (OSNs), but its functional role in this cell type has never been addressed. STOML3 is also expressed in dorsal root ganglia neurons, where it has been shown to be required for normal touch sensation. Here, we extended previous results indicating that STOML3 is mainly expressed in the knob and proximal cilia of OSNs. We additionally showed that mice lacking STOML3 have a morphologically normal olfactory epithelium. Because of its presence in the cilia, together with known olfactory transduction components, we hypothesized that STOML3 could be involved in modulating odorant responses in OSNs. To investigate the functional role of STOML3, we performed loose patch recordings from wild-type (WT) and Stoml3 knock-out (KO) OSNs. We found that spontaneous mean firing activity was lower with additional shift in interspike intervals (ISIs) distributions in Stoml3 KOs compared with WT neurons. Moreover, the firing activity in response to stimuli was reduced both in spike number and duration in neurons lacking STOML3 compared with WT neurons. Control experiments suggested that the primary deficit in neurons lacking STOML3 was at the level of transduction and not at the level of action potential generation. We conclude that STOML3 has a physiological role in olfaction, being required for normal sensory encoding by OSNs.

Enhanced Signal Detection by Adaptive Decorrelation of Interspike Intervals.

Spike trains with negative interspike interval (ISI) correlations, in which long/short ISIs are more likely followed by short/long ISIs, are common in many neurons. They can be described by stochastic models with a spike-triggered adaptation variable. We analyze a phenomenon in these models where such statistically dependent ISI sequences arise in tandem with quasi-statistically independent and identically distributed (quasi-IID) adaptation variable sequences. The sequences of adaptation states and resulting ISIs are linked by a nonlinear decorrelating transformation. We establish general conditions on a family of stochastic spiking models that guarantee this quasi-IID property and establish bounds on the resulting baseline ISI correlations. Inputs that elicit weak firing rate changes in samples with many spikes are known to be more detectible when negative ISI correlations are present because they reduce spike count variance; this defines a variance-reduced firing rate coding benchmark. We performed a Fisher information analysis on these adapting models exhibiting ISI correlations to show that a spike pattern code based on the quasi-IID property achieves the upper bound of detection performance, surpassing rate codes with the same mean rate-including the variance-reduced rate code benchmark-by 20% to 30%. The information loss in rate codes arises because the benefits of reduced spike count variance cannot compensate for the lower firing rate gain due to adaptation. Since adaptation states have similar dynamics to synaptic responses, the quasi-IID decorrelation transformation of the spike train is plausibly implemented by downstream neurons through matched postsynaptic kinetics. This provides an explanation for observed coding performance in sensory systems that cannot be accounted for by rate coding, for example, at the detection threshold where rate changes can be insignificant.

Early life maternal deprivation attenuates morphine induced inhibition in lateral paragigantocellularis neurons in adult rats

Early life stress can serve as one of the principle sources leading to individual differences in confronting challenges throughout the lifetime. Maternal deprivation (MD), a model of early life stress, can cause persistent alterations in brain function, and it may constitute a risk factor for later incidence of drug addiction. It is becoming more apparent that early life MD predisposes opiate abuse in adulthood. Although several behavioral and molecular studies have addressed this issue, changes in electrophysiological features of the neurons are yet to be understood. The lateral paragigantocellularis (LPGi) nucleus, which participates in the mediation of opiate dependence and withdrawal, may be susceptible to modifications following MD. This study sought to find whether early life MD can alter the discharge activity of LPGi neurons and their response to acute morphine administration in adult rats.Male Wistar rats experienced MD on postnatal days (PNDs) 1–14 for three h per day. Afterward, they were left undisturbed until PND 70, during which the extracellular activities of LPGi neurons were recorded in anesthetized animals at baseline and in response to acute morphine.In both MD and control groups, acute morphine administration induced heterogeneous (excitatory, inhibitory, and no effect) responses in LPGi neurons. At baseline recording, the interspike interval variability of the LPGi neurons was attenuated in both inhibitory and excitatory responses in animals with the history of MD. The extent of morphine-induced discharge inhibition was also lower in deprived animals compared to the control group.These findings suggest that early life MD induces long-term alterations in LPGi neuronal activity in response to acute administration of morphine. Therefore, the MD may alter the vulnerability to develop opiate abuse in adulthood.

Firing statistics in the bistable regime of neurons with homoclinic spike generation.

Neuronal voltage dynamics of regularly firing neurons typically has one stable attractor: either a fixed point (like in the subthreshold regime) or a limit cycle that defines the tonic firing of action potentials (in the suprathreshold regime). In two of the three spike onset bifurcation sequences that are known to give rise to all-or-none type action potentials, however, the resting-state fixed point and limit cycle spiking can coexist in an intermediate regime, resulting in bistable dynamics. Here, noise can induce switches between the attractors, i.e., between rest and spiking, and thus increase the variability of the spike train compared to neurons with only one stable attractor. Qualitative features of the resulting spike statistics depend on the spike onset bifurcations. This paper focuses on the creation of the spiking limit cycle via the saddle-homoclinic orbit (HOM) bifurcation and derives interspike interval (ISI) densities for a conductance-based neuron model in the bistable regime. The ISI densities of bistable homoclinic neurons are found to be unimodal yet distinct from the inverse Gaussian distribution associated with the saddle-node-on-invariant-cycle bifurcation. It is demonstrated that for the HOM bifurcation the transition between rest and spiking is mainly determined along the downstroke of the action potential-a dynamical feature that is not captured by the commonly used reset neuron models. The deduced spike statistics can help to identify HOM dynamics in experimental data.

Transition from noise-induced to self-sustained current spiking generated by a NbOx thin film threshold switch

A transition to self-sustained current oscillations was investigated in a circuit with a NbOx thin film device, acting as an artificial neuron. Above a threshold of the applied voltage, the circuit begins to demonstrate persistent but rather random current spiking, which becomes more regular with increasing applied voltage. Experimental measurements reveal two scaling regions of the interspike interval dependence on source voltage: an initial logarithmic dependence, which transitions to a power law with an exponent of -1/2. Using a numerical model of the artificial neuron circuit, we observe good agreement with our experimental data. We show that the logarithmic scaling behavior is associated with noise-induced spiking, while the power law is attributed to noisy self-sustained oscillations, which would exist in the system even with the absence of noise. These findings stress the importance of noise in the dynamics of NbOx threshold switches and shed light on their spiking response to variation of the input signals. The reported approach to spiking control in NbOx artificial oscillation neurons can help to develop an optimal design for neuromorphic neural networks and oscillator-based computing systems.

Evidence of two modes of spiking evoked in human firing motoneurones by Ia afferent electrical stimulation.

Neurone firing behaviour is a result of complex interaction between synaptic inputs and cellular intrinsic properties. Intriguing firing behaviour, delayed spiking, was shown in some neurones, in particular, in cat neocortical neurones and rat pyramidal hippocampal neurones. In contrast, the similar spiking mode was not reported for animal spinal motoneurones. In the present study, an attempt was made to look for possible evidence of delayed spiking in human motoneurones firing within the low-frequency, sub-primary range, characteristic for voluntary muscle contractions and postural tasks. Forty-seven firing motor units (MUs) were analyzed in ten experiments on three muscles (the flexor carpi ulnaris, the tibialis anterior, and the abductor pollicis brevis) in four healthy humans. Single MUs were activated by gentle voluntary muscle contractions. MU peri-stimulus time histograms, durations of inter-spike intervals, and motoneurone excitability changes within a target interspike interval were analyzed. It was found that during testing the firing motoneurone excitability by small, transient excitatory Ia afferent volley, depending firstly on volley timing within a target interspike interval and excitatory volley strength, the same motoneurone displayed either the direct short-latency response (the H-reflex) or the delayed response (with prolonged and variable latency). Thus, the findings, for the first time, provide evidence for a possibility of two modes of spiking in firing motoneurones. Methods of the estimation of delayed responses and their possible functional significance are discussed. It is emphasized that, for understanding of this issue, the integration of data from studies on experimental animals and humans is desirable.

Effects of datumetine on hippocampal NMDAR activity.

The usage (abuse) of Datura metel is becoming increasingly worrisome among the Nigerian populace especially among the youth considering its side effects such as hallucination. This work was designed to identify the phytochemicals in datura plant that potentially interact with NMDAR as it affects the electrical and memory activities of the brain. Ligand-protein interaction was assessed using autodock vina to identify phytochemicals that can interact with NMDAR. Datumetine was found to have the best interaction fit with NMDAR at both allosteric and orthosteric binding sites. Furthermore, using electrophysiological, behavioural and western blotting techniques, it was observed that the administration of datumetine positively modulates the NMDAR current by prolonging burst duration and interspike interval, induces seizures in C57BL/6 mice. Acute exposure leads to memory deficit on NOR and Y-maze test while immunoblotting results showed increased expression of GluN1 and CamKIIα while pCamKIIα-T286, CREB and BDNF were downregulated. The results showed that the memory deficit seen in datura intoxication is possibly the effects of datumetine on NMDAR.

Firing patterns and bifurcation analysis of neurons under electromagnetic induction

<p style='text-indent:20px;'>Based on the three-dimensional endocrine neuron model, a four-dimensional endocrine neuron model was constructed by introducing the magnetic flux variable and induced current according to the law of electromagnetic induction. Firstly, the codimension-one bifurcation and Interspike Intervals (ISIs) analysis were applied to study the bifurcation structure with respect to external stimuli and parameter <inline-formula><tex-math id="M1">$ k_0 $</tex-math></inline-formula>, and two dynamical behaviors were found: period-adding and period-doubling bifurcation leading to chaos. Besides, Hopf bifurcation was specially discussed corresponding to the transformation of the state. Secondly, the different firing patterns such as regular bursting, subthreshold oscillations, fast spiking, mixed-mode oscillations (MMOs) etc. can be observed by changing the external stimuli and the induced current. The neuron model presented more firing activities under strong coupling strength. Finally, the codimension-two bifurcation analysis shown more details of bifurcation. At the same time, the Bogdanov-Takens bifurcation point was also analyzed and three bifurcation curves were derived.</p>

Noise induces continuous and noncontinuous transitions in neuronal interspike intervals range

Noise appears in the brain due to various sources, such as ionic channel fluctuations and synaptic events. They affect the activities of the brain and influence neuron action potentials. Stochastic differential equations have been used to model firing patterns of neurons subject to noise. In this work, we consider perturbing noise in the adaptive exponential integrate-and-fire (AEIF) neuron. The AEIF is a two- dimensional model that describes different neuronal firing patterns by varying its parameters. Noise is added in the equation related to the membrane potential. We show that a noise current can induce continuous and noncontinuous transitions in neuronal interspike intervals. Moreover, we show that the noncontinuous transition occurs mainly for parameters close to the border between tonic spiking and burst activities of the neuron without noise

Maternal immune activation in rats attenuates the excitability of monoamine-secreting neurons in adult offspring in a sex-specific way

Higher risk of depression and schizophrenia in descendants of mothers experienced acute infection during the pregnancy has been reported. Since monoamines are fundamental in mentioned psychopathologies, it is possible that maternal immune activation leads to impaired functioning of serotonin (5-HT), noradrenaline, and dopamine neurons in offspring. To test this hypothesis, we examined the effect of maternal immune activation by lipopolysaccharide (LPS) in rats on the excitability of monoamine-secreting neurons in the offspring. LPS was administered during days 15–19 of the gestation in the rising doses of 20–80 µg/kg; control dams received vehicle. During days 53–63 postpartum, rats were anesthetized and electrodes were inserted into the dorsal raphe nucleus, locus coeruleus, and ventral tegmental area for in vivo excitability assessment of 5-HT, noradrenaline, and dopamine neurons. Maternal immune activation suppressed the firing rate of 5-HT neurons in both sexes and stimulated the firing rate of dopamine neurons in males. Decrease in the firing rate of 5-HT neurons was accompanied with an increase, and increase in the firing rate of dopamine neurons with a decrease, in the density of spontaneously active cells. Maternal immune activation also decreased the variability of interspike intervals in 5-HT and dopamine neurons. It is possible that the alteration of excitability of 5-HT and dopamine neurons by maternal immune activation is involved in the psychopathologies induced by infectious disease during the pregnancy. Stimulation of dopamine excitability in males might be a compensatory mechanism secondary to the maternal immune challenge-induced suppression of 5-HT neurons.

Estimation of Synaptic Activity during Neuronal Oscillations

In the study of brain connectivity, an accessible and convenient way to unveil local functional structures is to infer the time trace of synaptic conductances received by a neuron by using exclusively information about its membrane potential (or voltage). Mathematically speaking, it constitutes a challenging inverse problem: it consists in inferring time-dependent parameters (synaptic conductances) departing from the solutions of a dynamical system that models the neuron’s membrane voltage. Several solutions have been proposed to perform these estimations when the neuron fluctuates mildly within the subthreshold regime, but very few methods exist for the spiking regime as large amplitude oscillations (revealing the activation of complex nonlinear dynamics) hinder the adaptability of subthreshold-based computational strategies (mostly linear). In a previous work, we presented a mathematical proof-of-concept that exploits the analytical knowledge of the period function of the model. Inspired by the relevance of the period function, in this paper we generalize it by providing a computational strategy that can potentially adapt to a variety of models as well as to experimental data. We base our proposal on the frequency versus synaptic conductance curve (f−gsyn), derived from an analytical study of a base model, to infer the actual synaptic conductance from the interspike intervals of the recorded voltage trace. Our results show that, when the conductances do not change abruptly on a time-scale smaller than the mean interspike interval, the time course of the synaptic conductances is well estimated. When no base model can be cast to the data, our strategy can be applied provided that a suitable f−gsyn table can be experimentally constructed. Altogether, this work opens new avenues to unveil local brain connectivity in spiking (nonlinear) regimes.

Cannabinoid CB1 receptor mediates METH-induced electrophysiological and morphological alterations in cerebellum Purkinje cells.

Our previous studies on cannabinoid type1 receptor (CB1R) activation on Methamphetamine (METH)-induced neurodegeneration and locomotion impairments in male rats suggest an interaction between CB1Rs and METH. However, the role of these receptors in METH-neurotoxicity has not been fully identified. Therefore, the purpose of the present study is to investigate the involvement of CB1Rs in these effects. We conducted an electrophysiological study to evaluate functional interactions between METH and CB1Rs using whole-cell patch current clamp recording. Furthermore, we designed the Nissl staining protocol to assess the effect of METH on the basic cerebellar Purkinje cell structure. Our findings revealed that METH significantly increased the action potential half-width, spontaneous interspike intervals, first spike latency, and decreased the rebound action potential and spontaneous firing frequency. Using CB1R agonist and antagonist, our results showed a significant interaction with some of the electrophysiological alterations induced by METH. Further, Nissl staining revealed that the exposure to the combination of METH and SR141716A resulted in the necrotic cell death. Results of the current study raises the possibility that METH consumption profoundly affect the intrinsic membrane properties of cerebellar Purkinje neurons and cannabinoid system manipulations may counteract some of these effects. In summary, our findings provide further insights into the modulatory role of the endocannabinoid system in METH-induced neurologic changes, which can be used in the development of potential therapeutic interventions for METH dependence.

Inter-spike mitochondrial Ca2+ release enhances high frequency synaptic transmission.

Presynaptic mitochondria not only absorb but also release Ca2+ during high frequency stimulation (HFS) when presynaptic [Ca2+ ] is kept low (<500nm) by high cytosolic Ca2+ buffer or strong plasma membrane calcium clearance mechanisms under physiological external [Ca2+ ]. Mitochondrial Ca2+ release (MCR) does not alter the global presynaptic Ca2+ transients. MCR during HFS enhances short-term facilitation and steady state excitatory postsynaptic currents by increasing vesicular release probability. The intra-train MCR may provide residual calcium at interspike intervals, and thus support high frequency neurotransmission at central glutamatergic synapses. Emerging evidence indicates that mitochondrial Ca2+ buffering contributes to local regulation of synaptic transmission. It is unknown, however, whether mitochondrial Ca2+ release (MCR) occurs during high frequency synaptic transmission. Confirming the previous notion that 2μm tetraphenylphosphonium (TPP+ ) is a specific inhibitor of the mitochondrial Na+ /Ca2+ exchanger (mNCX), we studied the role of MCR via mNCX in short-term plasticity during high frequency stimulation (HFS) at the calyx of Held synapse of the rat. TPP+ reduced short-term facilitation (STF) and steady state excitatory postsynaptic currents during HFS at mature calyx synapses under physiological extracellular [Ca2+ ] ([Ca2+ ]o =1.2mm), but not at immature calyx or at 2mm [Ca2+ ]o . The inhibitory effects of TPP+ were stronger at synapses with morphologically complex calyces harbouring many swellings and at 32°C than at simple calyx synapses and at room temperature. These effects of TPP+ on STF were well correlated with those on the presynaptic mitochondrial [Ca2+ ] build-up during HFS. Mitochondrial [Ca2+ ] during HFS was increased by TPP+ at mature calyces under 1.2mm [Ca2+ ]o , and further enhanced at 32°C, but not under 2mm [Ca2+ ]o or at immature calyces. The close correlation of the effects of TPP+ on mitochondrial [Ca2+ ] with those on STF suggests that mNCX contributes to STF at the calyx of Held synapses. The intra-train MCR enhanced vesicular release probability without altering global presynaptic [Ca2+ ]. Our results suggest that MCR during HFS elevates local [Ca2+ ] near synaptic sites at interspike intervals to enhance STF and to support stable synaptic transmission under physiological [Ca2+ ]o .

Calcium Oscillations in Pancreatic α-cells Rely on Noise and ATP-Driven Changes in Membrane Electrical Activity.

In pancreatic α-cells, intracellular Ca2+ ([Ca2+]i) acts as a trigger for secretion of glucagon, a hormone that plays a key role in blood glucose homeostasis. Intracellular Ca2+ dynamics in these cells are governed by the electrical activity of voltage-gated ion channels, among which ATP-sensitive K+ (KATP) channels play a crucial role. In the majority of α-cells, the global Ca2+ response to lowering external glucose occurs in the form of oscillations that are much slower than electrical activity. These Ca2+ oscillations are highly variable as far as inter-spike intervals, shapes and amplitudes are concerned. Such observations suggest that Ca2+ dynamics in α-cells are much influenced by noise. Actually, each Ca2+ increase corresponds to multiple cycles of opening/closing of voltage gated Ca2+ channels that abruptly become silent, before the occurrence of another burst of activity a few tens of seconds later. The mechanism responsible for this intermittent activity is currently unknown. In this work, we used computational modeling to investigate the mechanism of cytosolic Ca2+ oscillations in α-cells. Given the limited population of KATP channels in this cell type, we hypothesized that the stochastic activity of these channels could play a key role in the sporadic character of the action potentials. To test this assumption, we extended a previously proposed model of the α-cells electrical activity (Diderichsen and Göpel, 2006) to take Ca2+ dynamics into account. Including molecular noise on the basis of a Langevin type description as well as realistic dynamics of opening and closing of KATP channels, we found that stochasticity at the level of the activity of this channel is on its own not able to produce Ca2+ oscillations with a time scale of a few tens of seconds. However, when taking into account the intimate relation between Ca2+ and ATP changes together with the intrinsic noise at the level of the KATP channels, simulations displayed Ca2+ oscillations that are compatible with experimental observations. We analyzed the detailed mechanism and used computational simulations to identify the factors that can affect Ca2+ oscillations in α-cells.

Firing patterns of the CA1 pyramidal neuron with geometric singular perturbation: a model study

An investigation of CA1 pyramidal model is an important issue for applications, which is intimately related to the composition of ions in the extracellular environment and external stimulation. In this paper, it is demonstrated that the effects of different electrophysiological parameters such as muscarinic-sensitive potassium current activation variable and sustained sodium current inactivation variable on the firing sequence of model by numerical simulations. Furthermore, the paper also discusses that the temperature affects the firing of the CA1 model from direct current (DC) and alternating current (AC) stimuli. It is found that the model exhibits excellent spiking and bursting patterns, even chaotic patterns occur. Meanwhile, generalized mixed oscillations emerge in the model. Additionally, the firing modes are depicted by providing the response curve (RC), inter-spike interval curve (ISI), phase diagram curve (PDC) and the number of spikes per burst curve (NC). Mathematically, the paper elaborates the results which are presented to obtain two lower dimensional subsystems, which govern the fast and slow dynamics for giving insight into the dynamic behaviors of the full 5D system based on the geometric singular perturbation theory (GSPT). Particularly, we analyse the phase diagrams of the CA1 model to understand the properties better. The present results may contribute to further understand the information processing of the CA1 pyramidal neurons.

Cholinergic Modulation of Membrane Properties of Calyx Terminals in the Vestibular Periphery

Vestibular nerve afferents are divided into regular and irregular groups based on the variability of interspike intervals in their resting discharge. Most afferents receive inputs from bouton terminals that contact type II hair cells as well as from calyx terminals that cover the basolateral walls of type I hair cells. Calyces have an abundance of different subtypes of KCNQ (Kv7) potassium channels and muscarinic acetylcholine receptors (mAChRs) and receive cholinergic efferent inputs from neurons in the brainstem. We investigated whether mAChRs affected membrane properties and firing patterns of calyx terminals through modulation of KCNQ channel activity. Patch clamp recordings were performed from calyx terminals in central regions of the cristae of the horizontal and anterior canals in 13–26 day old Sprague-Dawley rats. KCNQ mediated currents were observed as voltage sensitive currents with slow kinetics (activation and deactivation), resulting in spike frequency adaptation so that calyces at best fired a single action potential at the beginning of a depolarizing step. Activation of mAChRs by application of oxotremorine methiodide or inhibition of KCNQ channels by linopirdine dihydrochloride decreased voltage activated currents by ∼30%, decreased first spike latencies by ∼40%, resulted in action potential generation in response to smaller current injections and at lower (i.e., more hyperpolarized) membrane potentials, and increased the number of spikes fired during depolarizing steps. Interestingly, some of the calyces showed spontaneous discharge in the presence of these drugs. Together, these findings suggest that cholinergic efferents can modulate the response properties and encoding of head movements by afferents.

Interspike intervals within retinal spike bursts combinatorially encode multiple stimulus features.

Neurons in various regions of the brain generate spike bursts. While the number of spikes within a burst has been shown to carry information, information coding by interspike intervals (ISIs) is less well understood. In particular, a burst with k spikes has k-1 intraburst ISIs, and these k-1 ISIs could theoretically encode k-1 independent values. In this study, we demonstrate that such combinatorial coding occurs for retinal bursts. By recording ganglion cell spikes from isolated salamander retinae, we found that intraburst ISIs encode oscillatory light sequences that are much faster than the light intensity modulation encoded by the number of spikes. When a burst has three spikes, the two intraburst ISIs combinatorially encode the amplitude and phase of the oscillatory sequence. Analysis of trial-to-trial variability suggested that intraburst ISIs are regulated by two independent mechanisms responding to orthogonal oscillatory components, one of which is common to bursts with a different number of spikes. Therefore, the retina encodes multiple stimulus features by exploiting all degrees of freedom of burst spike patterns, i.e., the spike number and multiple intraburst ISIs.

Mixed-mode self-oscillations, stochastic excitability, and coherence resonance in flows of highly concentrated suspensions

Complex mixed-mode oscillatory regimes in flows of concentrated suspensions are studied on the base of the nonlinear dynamical model. A mechanism of the generation of such regimes is associated with the N-shaped flow curve which reflects the dependence of the shear rate on the shear stress. In the zone of the unstable equilibria, amplitude and frequency characteristics of mixed-mode self-sustained oscillations are investigated. A transformation of quasi-harmonic oscillations to non-harmonic ones under increase of the stiffness of the flow curve is discussed. In the zone of the stable equilibria, a phenomenon of stochastic excitement of spike oscillations is studied by the analytical stochastic sensitivity method along with direct numerical simulations. For these mixed-mode stochastic oscillations, a parametric analysis of statistics of interspike intervals is carried out and a phenomenon of coherence resonance is discussed.

Frequency-dependent spike-pattern changes in motor cortex during thalamic deep brain stimulation.

The cerebellar-receiving area of the motor thalamus is the primary anatomical target for treating essential tremor with deep brain stimulation (DBS). Although neuroimaging studies have shown that higher stimulation frequencies in this target correlate with increased cortical metabolic activity, less is known about the cellular-level functional changes that occur in the primary motor cortex (M1) with thalamic stimulation and how these changes depend on the frequency of DBS. In this study, we used a preclinical animal model of DBS to collect single-unit spike recordings in M1 before, during, and after DBS targeting the cerebellar-receiving area of the motor thalamus (VPLo, nucleus ventralis posterior lateralis pars oralis). The effects of VPLo-DBS on M1 spike rates, interspike interval entropy, and peristimulus phase-locking were compared across stimulus pulse train frequencies ranging from 10 to 130 Hz. Although VPLo-DBS modulated the spike rates of 20-50% of individual M1 cells in a frequency-dependent manner, the population-level average spike rate only weakly depended on stimulation frequency. In contrast, the population-level entropy measure showed a pronounced decrease with high-frequency stimulation, caused by a subpopulation of cells that exhibited strong phase-locking and general spike-pattern regularization. Contrarily, low-frequency stimulation induced an entropy increase (spike-pattern disordering) in a relatively large portion of the recorded population, which diminished with higher stimulation frequencies. These results also suggest that changes in phase-locking and spike-pattern entropy are not necessarily equivalent pattern phenomena, but rather that they should both be weighed when quantifying stimulation-induced spike-pattern changes.NEW & NOTEWORTHY The network mechanisms of thalamic deep brain stimulation (DBS) are not well understood at the cellular level. This study investigated the neuronal firing rate and pattern changes in the motor cortex resulting from stimulation of the cerebellar-receiving area of the motor thalamus. We showed that there is a nonintuitive relationship between general entropy-based spike-pattern measures and phase-locked regularization to DBS.

Encoding specificity of scale-free spiking neural network under different external stimulations

Neural information coding is the foundation of information processing in the nervous system. The specificity of coding is the key issue of efficiently realizing complex cognition functions. In this study, a scale-free spiking neural network (SFSNN) is constructed based on synaptic plasticity and scale-free topology. The time coding properties of the SFSNN under different intensities of different stimulations including Gauss stimulation, impulse stimulation, and AC electric field stimulation are analyzed. On this basis, the specificity of time coding and the mechanism of time coding are studied emphatically. The experimental results show that: (1) Under each kind of stimulation, the inter-spike interval (ISI) is decreased, and the stronger the stimulation intensity is, the smaller the ISI is. (2) The time coding patterns have high similarity under same kind of stimulation, which is verified by the cosine similarity algorithm; the time coding patterns have high difference under different kind of stimulations, which is verified by the K-means clustering algorithm. Therefore, the time coding specificity is verified by the algorithms. (3) The relationship between the synaptic plasticity and time coding is established based on the Pearson correlation coefficient. The dynamic regulation of synaptic plasticity is significantly correlated with time coding under each kind of stimulation, which implies that the dynamic regulation of synaptic plasticity is the intrinsic factor of time coding mechanism.