Simple Spike Research Articles

Geometric analysis of mixed-mode oscillations in a model of electrical activity in human beta-cells

Human pancreatic beta-cells may exhibit complex mixed-mode oscillatory electrical activity, which underlies insulin secretion. A recent biophysical model of human beta-cell electrophysiology can simulate such bursting behavior, but a mathematical understanding of the model’s dynamics is still lacking. Here we exploit time-scale separation to simplify the original model to a simpler three-dimensional model that retains the behavior of the original model and allows us to apply geometric singular perturbation theory to investigate the origin of mixed-mode oscillations. Changing a parameter modeling the maximal conductance of a potassium current, we find that the reduced model possesses a singular Hopf bifurcation that results in small-amplitude oscillations, which go through a period-doubling sequence and chaos until the birth of a large-scale return mechanism and bursting dynamics. The theory of folded node singularities provide insight into the bursting dynamics further away from the singular Hopf bifurcation and the eventual transition to simple spiking activity. Numerical simulations confirm that the insight obtained from the analysis of the reduced model can be lifted back to the original model.

A model of cortical timbre classification using spike latency coding

Earlier modeling studies of spiking neural networks with conduction delays have shown that temporally precise, distributed spike patterns (polychronous groups) contain more information about timbral distinctions than firing rates. Additionally, experimental work in auditory cortex has suggested that the initial onset of firing activity is especially important for encoding timbre, an observation that is in accordance with psychoacoustical evidence that the onset characteristics of a stimulus can have a profound effect on the perception of timbre. These observations are combined in a model that uses spike latency to make timbral classifications. A simplified spiking model of the subcortical auditory system is connected to a reservoir of spiking point neurons with cortex-like connectivity statistics and conduction delays. Stimuli are presented to the model in an unsupervised manner, and synaptic strengths are adapted via a spike-timing-dependent plasticity mechanism. After training, a stochastic search algorithm is used to find stimulus-triggered firing patterns generated in the reservoir, the firing latency of which can be used to make accurate timbral categorizations of novel stimuli. The stimuli consist of FM-synthesized instrument sounds (two categories) with varying pitches, demonstrating the model’s ability to learn timbral distinctions in a manner invariant with respect to changes of pitch.

Anoctamin 2-chloride channels reduce simple spike activity and mediate inhibition at elevated calcium concentration in cerebellar Purkinje cells.

Modulation of neuronal excitability is a prominent way of shaping the activity of neuronal networks. Recent studies highlight the role of calcium-activated chloride currents in this context, as they can both increase or decrease excitability. The calcium-activated chloride channel Anoctamin 2 (ANO2 alias TMEM16B) has been described in several regions of the mouse brain, including the olivo-cerebellar system. In inferior olivary neurons, ANO2 was proposed to increase excitability by facilitating the generation of high-threshold calcium spikes. An expression of ANO2 in cerebellar Purkinje cells was suggested, but its role in these neurons remains unclear. In the present study, we confirmed the expression of Ano2 mRNA in Purkinje cells and performed electrophysiological recordings to examine the influence of ANO2-chloride channels on the excitability of Purkinje cells by comparing wildtype mice to mice lacking ANO2. Recordings were performed in acute cerebellar slices of adult mice, which provided the possibility to study the role of ANO2 within the cerebellar cortex. Purkinje cells were uncoupled from climbing fiber input to assess specifically the effect of ANO2 channels on Purkinje cell activity. We identified an attenuating effect of ANO2-mediated chloride currents on the instantaneous simple spike activity both during strong current injections and during current injections close to the simple spike threshold. Moreover, we report a reduction of inhibitory currents from GABAergic interneurons upon depolarization, lasting for several seconds. Together with the role of ANO2-chloride channels in inferior olivary neurons, our data extend the evidence for a role of chloride-dependent modulation in the olivo-cerebellar system that might be important for proper cerebellum-dependent motor coordination and learning.

Small universal spiking neural P systems with dendritic/axonal delays and dendritic trunk/feedback

In spiking neural P (SN P) systems, neurons are interconnected by means of synapses, and they use spikes to communicate with each other. However, in biology, the complex structure of dendritic tree is also an important part in the communication scheme between neurons since these structures are linked to advanced neural process such as learning and memory formation. In this work, we present a new variant of the SN P systems inspired by diverse dendrite and axon phenomena such as dendritic feedback, dendritic trunk, dendritic delays and axonal delays, respectively. This new variant is referred to as a spiking neural P system with dendritic and axonal computation (DACSN P system). Specifically, we include experimentally proven biological features in the current SN P systems to reduce the computational complexity of the soma by providing it with stable firing patterns through dendritic delays, dendritic feedback and axonal delays. As a consequence, the proposed DACSN P systems use the minimum number of synapses and neurons with simple and homogeneous standard spiking rules. Here, we study the computational capabilities of a DACSN P system. In particular, we prove that DACSN P systems with dendritic and axonal behavior are universal as both number-accepting/generating devices. In addition, we constructed a small universal SN P system using 39 neurons with standard spiking rules to compute any Turing computable function.

Cerebellar Purkinje cells can differentially modulate coherence between sensory and motor cortex depending on region and behavior

Activity of sensory and motor cortices is essential for sensorimotor integration. In particular, coherence between these areas may indicate binding of critical functions like perception, motor planning, action, or sleep. Evidence is accumulating that cerebellar output modulates cortical activity and coherence, but how, when, and where it does so is unclear. We studied activity in and coherence between S1 and M1 cortices during whisker stimulation in the absence and presence of optogenetic Purkinje cell stimulation in crus 1 and 2 of awake mice, eliciting strong simple spike rate modulation. Without Purkinje cell stimulation, whisker stimulation triggers fast responses in S1 and M1 involving transient coherence in a broad spectrum. Simultaneous stimulation of Purkinje cells and whiskers affects amplitude and kinetics of sensory responses in S1 and M1 and alters the estimated S1-M1 coherence in theta and gamma bands, allowing bidirectional control dependent on behavioral context. These effects are absent when Purkinje cell activation is delayed by 20 ms. Focal stimulation of Purkinje cells revealed site specificity, with cells in medial crus 2 showing the most prominent and selective impact on estimated coherence, i.e., a strong suppression in the gamma but not the theta band. Granger causality analyses and computational modeling of the involved networks suggest that Purkinje cells control S1-M1 phase consistency predominantly via ventrolateral thalamus and M1. Our results indicate that activity of sensorimotor cortices can be dynamically and functionally modulated by specific cerebellar inputs, highlighting a widespread role of the cerebellum in coordinating sensorimotor behavior.

Purkinje Cell Activity Determines the Timing of Sensory-Evoked Motor Initiation

SummaryCerebellar neurons can signal sensory and motor events, but their role in active sensorimotor processing remains unclear. We record and manipulate Purkinje cell activity during a task that requires mice to rapidly discriminate between multisensory and unisensory stimuli before motor initiation. Neuropixels recordings show that both sensory stimuli and motor initiation are represented by short-latency simple spikes. Optogenetic manipulation of short-latency simple spikes abolishes or delays motor initiation in a rate-dependent manner, indicating a role in motor initiation and its timing. Two-photon calcium imaging reveals task-related coherence of complex spikes organized into conserved alternating parasagittal stripes. The coherence of sensory-evoked complex spikes increases with learning and correlates with enhanced temporal precision of motor initiation. These results suggest that both simple spikes and complex spikes govern sensory-driven motor initiation: simple spikes modulate its latency, and complex spikes refine its temporal precision, providing specific cellular substrates for cerebellar sensorimotor control.

Corticotrophin-Releasing Factor Modulates the Facial Stimulation-Evoked Molecular Layer Interneuron-Purkinje Cell Synaptic Transmission in vivo in Mice.

Corticotropin-releasing factor (CRF) is an important neuromodulator in central nervous system that modulates neuronal activity via its receptors during stress responses. In cerebellar cortex, CRF modulates the simple spike (SS) firing activity of Purkinje cells (PCs) has been previously demonstrated, whereas the effect of CRF on the molecular layer interneuron (MLI)–PC synaptic transmission is still unknown. In this study, we examined the effect of CRF on the facial stimulation–evoked cerebellar cortical MLI-PC synaptic transmission in urethane-anesthetized mice by in vivo cell-attached recording, neurobiotin juxtacellular labeling, immunohistochemistry techniques, and pharmacological method. Cell-attached recordings from cerebellar PCs showed that air-puff stimulation of ipsilateral whisker pad evoked a sequence of tiny parallel fiber volley (N1) followed by MLI-PC synaptic transmission (P1). Microapplication of CRF in cerebellar cortical molecular layer induced increases in amplitude of P1 and pause of SS firing. The CRF decreases in amplitude of P1 waveform were in a dose-dependent manner with the EC50 of 241 nM. The effects of CRF on amplitude of P1 and pause of SS firing were abolished by either a non-selective CRF receptor antagonist, α-helical CRF-(9-14), or a selective CRF-R1 antagonist, BMS-763534 (BMS, 200 nM), but were not prevented by a selective CRF-R2 antagonist, antisauvagine-30 (200 nM). Notably, application CRF not only induced a significant increase in spontaneous spike firing rate, but also produced a significant increase in the number of the facial stimulation–evoked action potential in MLIs. The effect of CRF on the activity of MLIs was blocked by the selective CRF-R1 antagonist, and the MLIs expressed the CRF-R1 imunoreactivity. These results indicate that CRF increases excitability of MLIs via CRF-R1, resulting in an enhancement of the facial stimulation–evoked MLI-PC synaptic transmission in vivo in mice.

Pogz deficiency leads to transcription dysregulation and impaired cerebellar activity underlying autism-like behavior in mice

Several genes implicated in autism spectrum disorder (ASD) are chromatin regulators, including POGZ. The cellular and molecular mechanisms leading to ASD impaired social and cognitive behavior are unclear. Animal models are crucial for studying the effects of mutations on brain function and behavior as well as unveiling the underlying mechanisms. Here, we generate a brain specific conditional knockout mouse model deficient for Pogz, an ASD risk gene. We demonstrate that Pogz deficient mice show microcephaly, growth impairment, increased sociability, learning and motor deficits, mimicking several of the human symptoms. At the molecular level, luciferase reporter assay indicates that POGZ is a negative regulator of transcription. In accordance, in Pogz deficient mice we find a significant upregulation of gene expression, most notably in the cerebellum. Gene set enrichment analysis revealed that the transcriptional changes encompass genes and pathways disrupted in ASD, including neurogenesis and synaptic processes, underlying the observed behavioral phenotype in mice. Physiologically, Pogz deficiency is associated with a reduction in the firing frequency of simple and complex spikes and an increase in amplitude of the inhibitory synaptic input in cerebellar Purkinje cells. Our findings support a mechanism linking heterochromatin dysregulation to cerebellar circuit dysfunction and behavioral abnormalities in ASD.

In vivo analysis of the spontaneous firing of cerebellar Purkinje cells in awake transgenic mice that model spinocerebellar ataxia type 2

Cerebellar Purkinje cells (PCs) fire spontaneously in a tonic mode, although the precision of this pacemaking activity is disturbed in many abnormal conditions involving cerebellar atrophy, such as many spinocerebellar ataxias (SCAs). In our previous studies we used the single-unit extracellular recording method to analyze spontaneous PC firing in vivo in the anesthetized SCA2-58Q transgenic mice. We realized that PCs from aging SCA2-58Q mice fire much less regularly compared to PCs from their wild type (WT) littermates and this abnormal activity can be reversed with an intraperitoneal (i. p.) injection of SK channel-positive modulator chlorzoxazone (CHZ). Here we used the same single-unit extracellular recording method to analyze the spontaneous firing in vivo in awake SCA2-58Q transgenic mice. For this purpose, we used the Mobile HomeCage (Neurotar, Finland) floating platform to immobilize the experimental animal's head during the recording sessions. We discovered that generally PCs from awake animals fired much more frequently and much less regularly than previously observed PCs from anesthetized animals. In vivo recordings from awake SCA2/WT mice revealed that complex spikes, which are generated by PCs in reply to the excitation coming by climbing fibers, as well as simple spikes, were much less frequent in SCA2 mice compared to their WT littermates. To test the effect of the SK channel positive modulation on the PCs firing activity in awake SCA2 mice and also the effect on their motor coordination, we started the CHZ trial in these mice. We discovered that the long-term i. p. injections of CHZ did not affect the spike generation in SCA2-58Q mice, however, they did recover the precision of this spontaneous pacemaking activity. Furthermore, we also showed that treatment with CHZ alleviated the age-dependent motor impairment in SCA2-58Q mice. We propose that the lack of precision in PC spike generation might be a key cause for the progression of ataxic symptoms in different SCAs and that the activation of calcium-activated potassium channels, including SK channels, can be used as a potential way to treat SCAs on the physiological level of the disease.

Cerebellar Cortex 4-12 Hz Oscillations and Unit Phase Relation in the Awake Rat.

Oscillations in the granule cell layer (GCL) of the cerebellar cortex have been related to behavior and could facilitate communication with the cerebral cortex. These local field potential (LFP) oscillations, strong at 4–12 Hz in the rodent cerebellar cortex during awake immobility, should also be an indicator of an underlying influence on the patterns of the cerebellar cortex neuronal firing during rest. To address this hypothesis, cerebellar cortex LFPs and simultaneous single-neuron activity were collected during LFP oscillatory periods in the GCL of awake resting rats. During these oscillatory episodes, different types of units across the GCL and Purkinje cell layers showed variable phase-relation with the oscillatory cycles. Overall, 74% of the Golgi cell firing and 54% of the Purkinje cell simple spike (SS) firing were phase-locked with the oscillations, displaying a clear phase relationship. Despite this tendency, fewer Golgi cells (50%) and Purkinje cell’s SSs (25%) showed an oscillatory firing pattern. Oscillatory phase-locked spikes for the Golgi and Purkinje cells occurred towards the peak of the LFP cycle. GCL LFP oscillations had a strong capacity to predict the timing of Golgi cell spiking activity, indicating a strong influence of this oscillatory phenomenon over the GCL. Phase-locking was not as prominent for the Purkinje cell SS firing, indicating a weaker influence over the Purkinje cell layer, yet a similar phase relation. Overall, synaptic activity underlying GCL LFP oscillations likely exert an influence on neuronal population firing patterns in the cerebellar cortex in the awake resting state and could have a preparatory neural network shaping capacity serving as a neural baseline for upcoming cerebellar operations.

Entrainment of cerebellar purkinje cells with directional AC electric fields in anesthetized rats

BackgroundTranscranial electrical stimulation (tES) shows promise to treat neurological disorders. Knowledge of how the orthogonal components of the electric field (E-field) alter neuronal activity is required for strategic placement of transcranial electrodes. Yet, essentially no information exists on this relationship for mammalian cerebellum in vivo, despite the cerebellum being a target for clinical tES studies. ObjectiveTo characterize how cerebellar Purkinje cell (PC) activity varies with the intensity, frequency, and direction of applied AC and DC E-fields. MethodsExtracellular recordings were obtained from vermis lobule 7 PCs in anesthetized rats. AC (2–100 Hz) or DC E-fields were generated in a range of intensities (0.75–30 mV/mm) in three orthogonal directions. Field-evoked PC simple spike activity was characterized in terms of firing rate modulation and phase-locking as a function of these parameters. t-tests were used for statistical comparisons. ResultsThe effect of applied E-fields was direction and intensity dependent, with rostrocaudally directed fields causing stronger modulations than dorsoventral fields and mediolaterally directed ones causing little to no effect, on average. The directionality dependent modulation suggests that PC is the primary cell type affected the most by electric stimulation, and this effect was probably given rise by a large dendritic tree and a soma. AC stimulation entrained activity in a frequency dependent manner, with stronger phase-locking to the stimulus cycle at higher frequencies. DC fields produced a modulation consisting of strong transients at current onset and offset with an intervening plateau. ConclusionOrientation of the exogenous E-field critically determines the modulation depth of cerebellar cortical output. With properly oriented fields, PC simple spike activity can strongly be entrained by AC fields, overriding the spontaneous firing pattern.

Climbing fiber synapses rapidly and transiently inhibit neighboring Purkinje cells via ephaptic coupling

Climbing fibers (CFs) from the inferior olive (IO) make strong excitatory synapses onto cerebellar Purkinje cell (PC) dendrites, and trigger distinctive responses known as complex spikes (CSs). We find that in awake mice, a CS in one PC suppresses conventional simple spikes (SSs) in neighboring PCs for several milliseconds. This involves a novel ephaptic coupling, in which an excitatory synapse generates large negative extracellular signals that nonsynaptically inhibit neighboring PCs. The distance dependence of CS-SS ephaptic signaling, combined with the known CF divergence, allows a single IO neuron to influence the output of the cerebellum by synchronously suppressing the firing of potentially over one hundred PCs. Optogenetic studies in vivo, and dynamic clamp studies in slice, indicate that such brief PC suppression, either as a result of ephaptic signaling or other mechanisms, can effectively promote firing in neurons in the deep cerebellar nuclei with remarkable speed and precision.

Fentanyl Inhibits Air Puff-Evoked Sensory Information Processing in Mouse Cerebellar Neurons Recorded in vivo.

Aim: To examine the effects of fentanyl, a potent mu-opioid receptor (MOR) agonist, on-air puff-evoked responses in Purkinje cells (PCs), and molecular layer interneurons (MLIs) using in vivo patch-clamp recordings in anesthetized mice.Methods: Male mice 6–8 weeks-old were anesthetized and fixed on a custom-made stereotaxic frame. The cerebellar surface was exposed and perfused with oxygenated artificial cerebrospinal fluid (ACSF). Patch-clamp recordings in the cell-attached mode were obtained from PCs and MLIs. Facial stimulation by air-puff of the ipsilateral whisker pad was performed through a pressurized injection system. Fentanyl citrate, CTOP, and H-89 dissolved in ACSF were perfused onto the cerebellar surface.Results: Fentanyl significantly inhibited the amplitude and area under the curve (AUC) of sensory stimulation-evoked inhibitory responses in PCs. Although fentanyl did not influence the frequency of simple spikes (SSs), it decreased the pause of SS. The IC50 of the fentanyl-induced suppression of the P1 response amplitude was 5.53 μM. The selective MOR antagonist CTOP abolished fentanyl-induced inhibitory responses in PCs. However, the application of CTOP alone increased the amplitude, AUC of P1, and the pause of SS. Notably, fentanyl significantly inhibited the tactile-evoked response of MLIs but did not affect their spontaneous firing. The fentanyl-induced decrease of inhibitory responses in PCs was partially prevented by a PKA inhibitor, H-89.Conclusions: These results suggest that fentanyl binds to MORs in MLIs to reduce GABAergic neurotransmission in MLI-PC projections and one potential mechanism is via modulation of the cAMP-PKA pathway.

Nanoscale Room-Temperature Multilayer Skyrmionic Synapse for Deep Spiking Neural Networks

Magnetic skyrmions have attracted considerable interest, especially after their recent experimental demonstration at room temperature in multilayers. The robustness, nanoscale size and non-volatility of skyrmions have triggered a substantial amount of research on skyrmion-based low-power, ultra-dense nanocomputing and neuromorphic systems such as artificial synapses. Room-temperature operation is required to integrate skyrmionic synapses in practical future devices. Here, we numerically propose a nanoscale skyrmionic synapse composed of magnetic multilayers that enables room-temperature device operation tailored for optimal synaptic resolution. We demonstrate that when embedding such multilayer skyrmionic synapses in a simple spiking neural network (SNN) with unsupervised learning via the spike-timing-dependent plasticity rule, we can achieve only a 78% classification accuracy in the MNIST handwritten data set under realistic conditions. We propose that this performance can be significantly improved to about 98.61% by using a deep SNN with supervised learning. Our results illustrate that the proposed skyrmionic synapse can be a potential candidate for future energy-efficient neuromorphic edge computing.

Multiple signals evoked by unisensory stimulation converge onto cerebellar granule and Purkinje cells in mice

The cerebellum receives signals directly from peripheral sensory systems and indirectly from the neocortex. Even a single tactile stimulus can activate both of these pathways. Here we report how these different types of signals are integrated in the cerebellar cortex. We used in vivo whole-cell recordings from granule cells and unit recordings from Purkinje cells in mice in which primary somatosensory cortex (S1) could be optogenetically inhibited. Tactile stimulation of the upper lip produced two-phase granule cell responses (with latencies of ~8 ms and 29 ms), for which only the late phase was S1 dependent. In Purkinje cells, complex spikes and the late phase of simple spikes were S1 dependent. These results indicate that individual granule cells combine convergent inputs from the periphery and neocortex and send their outputs to Purkinje cells, which then integrate those signals with climbing fiber signals from the neocortex.

Functional Convergence of Autonomic and Sensorimotor Processing in the Lateral Cerebellum

SummaryThe cerebellum is involved in the control of voluntary and autonomic rhythmic behaviors, yet it is unclear to what extent it coordinates these in concert. We studied Purkinje cell activity during unperturbed and perturbed respiration in lobules simplex, crus 1, and crus 2. During unperturbed (eupneic) respiration, complex spike and simple spike activity encode the phase of ongoing sensorimotor processing. In contrast, when the respiratory cycle is perturbed by whisker stimulation, mice concomitantly protract their whiskers and advance their inspiration in a phase-dependent manner, preceded by increased simple spike activity. This phase advancement of respiration in response to whisker stimulation can be mimicked by optogenetic stimulation of Purkinje cells and prevented by cell-specific genetic modification of their AMPA receptors, hampering increased simple spike firing. Thus, the impact of Purkinje cell activity on respiratory control is context and phase dependent, highlighting a coordinating role for the cerebellar hemispheres in aligning autonomic and sensorimotor behaviors.

A simple digital spiking neural network: Synchronization and spike-train approximation

<p style='text-indent:20px;'>This paper studies synchronization phenomena of spike-trains and approximation of target spike-trains in a simple network of digital spiking neurons. Repeating integrate-and-fire behavior between a periodic base signal and constant firing threshold, the neurons can generate various spike-trains. Connecting multiple neurons by cross-firing with delay, the network is constructed. The network can exhibit multi-phase synchronization of various spike-trains. Stability of the synchronization phenomena can be guaranteed theoretically. Applying a simple winner-take-all switching, the network can approximate target spike-trains automatically. In order to evaluate the approximation performance, we present two metrics: spike-position error and spike missing rate. Using the metrics, approximation capability of the network is investigated in typical target signals. Presenting an FPGA based hardware prototype, typical synchronization phenomenon and spike-train approximation are confirmed experimentally.

Toward Efficient Processing and Learning With Spikes: New Approaches for Multispike Learning.

Spikes are the currency in central nervous systems for information transmission and processing. They are also believed to play an essential role in low-power consumption of the biological systems, whose efficiency attracts increasing attentions to the field of neuromorphic computing. However, efficient processing and learning of discrete spikes still remain a challenging problem. In this article, we make our contributions toward this direction. A simplified spiking neuron model is first introduced with the effects of both synaptic input and firing output on the membrane potential being modeled with an impulse function. An event-driven scheme is then presented to further improve the processing efficiency. Based on the neuron model, we propose two new multispike learning rules which demonstrate better performance over other baselines on various tasks, including association, classification, and feature detection. In addition to efficiency, our learning rules demonstrate high robustness against the strong noise of different types. They can also be generalized to different spike coding schemes for the classification task, and notably, the single neuron is capable of solving multicategory classifications with our learning rules. In the feature detection task, we re-examine the ability of unsupervised spike-timing-dependent plasticity with its limitations being presented, and find a new phenomenon of losing selectivity. In contrast, our proposed learning rules can reliably solve the task over a wide range of conditions without specific constraints being applied. Moreover, our rules cannot only detect features but also discriminate them. The improved performance of our methods would contribute to neuromorphic computing as a preferable choice.

Leaky integrate-and-fire neurons based on perovskite memristor for spiking neural networks

Artificial neuron is an important part of constructing neuromorphic network in which information can be computed with high parallelism and efficiency like in the human brain. However, owing to the poor biological plausibility, artificial neurons based on traditional complementary metal-oxide-semiconductor (CMOS) platform fail to reveal the rich ion dynamics of the biological counterparts. Organic–inorganic halide perovskites (OHPs) are prospective for imitating the ion dynamics on the membranes of biological neurons because of its intrinsic ion migration. Herein, a diffusive CH 3 NH 3 PbI 3 (MAPbI 3 )-based memristor with superior amplitude-frequency characteristics and highly linear conductivity modulation for more than 1000 states have been fabricated for the construction of a leaky integrate-and-fire (LIF) bio-inspired neuron. The as-designed LIF model can successfully emulate the leakage, spatiotemporal integration and firing functions in a biological neuron. Moreover, by connecting LIF neurons with a 2*2 non-volatile Al 2 O 3 -based synaptic array, a simple spiking neural network (SNN) which is called the 3rd generation of neural network has been implemented at the hardware level to study the cognitive performance of the network. The SNN exhibits outstanding selective sensitivity to particular input sequence, indicating the excellent adaptability and versatility of the network for future applications of neuromorphic computing by utilizing novel ionotropic device. Herein, for the first time, a diffusive CH 3 NH 3 PbI 3 (MAPbI 3 )-based memristor with superior amplitude-frequency characteristics and highly linear conductivity modulation for more than 1000 states have been fabricated for the construction of a leaky integrate-and-fire (LIF) bio-inspired neuron. The as-designed LIF model can successfully emulate the leakage, spatiotemporal integration and firing functions in a biological neuron, indicating the great potential for neuromorphic computing. Furthermore, by connecting LIF neurons with a 2*2 non-volatile Al 2 O 3 -based synaptic array, a simple spiking neural network has been implemented at the hardware level to study the cognitive performance of the network. • The conductance states of MAPbI 3 -based memristor can be modulated linearly and consecutively for more than 1000 states. • The memristor exhibits superior amplitude-frequency response characteristics which may be also suitable for filter. • A leaky integrate-and-fire artificial neuron is implemented, and the leakage, spatiotemporal integration and firing functions are emulated successfully. • By combining the artificial neuron with an synaptic array, a simple spiking neural network has been implemented.

Complementary Metal‐Oxide Semiconductor and Memristive Hardware for Neuromorphic Computing

The ever‐increasing processing power demands of digital computers cannot continue to be fulfilled indefinitely unless there is a paradigm shift in computing. Neuromorphic computing, which takes inspiration from the highly parallel, low‐power, high‐speed, and noise‐tolerant computing capabilities of the brain, may provide such a shift. Many researchers from across academia and industry have been studying materials, devices, circuits, and systems, to implement some of the functions of networks of neurons and synapses to develop neuromorphic computing platforms. These platforms are being designed using various hardware technologies, including the well‐established complementary metal‐oxide semiconductor (CMOS), and emerging memristive technologies such as SiOx‐based memristors. Herein, recent progress in CMOS, SiOx‐based memristive, and mixed CMOS‐memristive hardware for neuromorphic systems is highlighted. New and published results from various devices are provided that are developed to replicate selected functions of neurons, synapses, and simple spiking networks. It is shown that the CMOS and memristive devices are assembled in different neuromorphic learning platforms to perform simple cognitive tasks such as classification of spike rate‐based patterns or handwritten digits. Herein, it is envisioned that what is demonstrated is useful to the unconventional computing research community by providing insights into advances in neuromorphic hardware technologies.