Heterosynaptic Plasticity Research Articles

Non-associative potentiation of proximal excitatory inputs to layer 2/3 pyramidal cells in rat visual cortex

Long-term changes of synaptic transmission can be induced by Hebbian-type homosynaptic mechanisms which require activation of both pre- and postsynapse and mediate associative learning, as well as by heterosynaptic mechanisms which do not require activation of the presynapse and are non-associative. The rules for induction of homosynaptic plasticity depend on the distance of the synapse from the soma. Does induction of heterosynaptic plasticity also depend on synaptic location? Here, we investigated heterosynaptic changes in pharmacologically isolated glutamatergic inputs arriving at either the proximal or the distal segments of the apical dendrite of layer 2/3 pyramidal neurons in rat visual cortex. We show that bursts of action potentials evoked without presynaptic stimulation induced potentiation of proximal inputs while having little effect on distal inputs. Such gradient of plasticity could be related to the attenuation of backpropagating action potentials along the dendrites. Thus, the location of the synapse on the dendritic tree is a determinant not only for homosynaptic but also for heterosynaptic plasticity.

CMOS-Compatible Single-Gated Memtransistor Having 3-D Bulk Channel Embedded with Quantum Well Memory Nodes for Fast Training of Deep Neural Network

Recently, three-terminal synaptic devices having gate, source, and drain electrodes have been actively researched to compensate for the poor reliability of two-terminal synaptic devices such as resistive random access memory (ReRAM) and phase change random access memory (PCRAM)1. Two-terminal devices inherently suffer from read disturbance problems, where the stored resistance state changes gradually during the read process of the artificial neural network2. In addition, two-terminal devices essentially require selection devices for performing the write (program or erase) and read process, which is limited to commercialization because matching of the electrical characteristics between the selection device and the synaptic device was extremely difficult3. Moreover, the training speed of artificial neural networks would degrade due to the constant on/off ratio of conductance of two-terminal synaptic devices.To solve this problem, the memtransistors that can change the conductance range of the channel with gate bias have been reported. However, most of the reported memtransistors employed 2-D materials such as MoS2, WSe2, and SnS2 as a channel layer, which is a limitation for uniform large-area thin film growth4–6. In other words, the memtransistors with a 2-D channel layer do not have CMOS compatibility.In this study, for the first time, we designed a CMOS-compatible single-gated memtransistor having an indium-gallium-zinc-oxide (IGZO) channel embedded with quantum well memory nodes via Au nanoparticles. The quantum well memory nodes were obtained by precisely designing the diameter of Au nanoparticles in the IGZO 3-D bulk channel and SiO2 gate oxide interfaces. In addition, the quantum well memory nodes using Au nanoparticles were investigated by an energy band diagram obtained from ultraviolet photoelectron spectroscopy (UPS) analysis of Au, IGZO, and Al source/drain electrodes. Thereby, the gate-tunable pinched hysteresis loops in the output curve of the designed memtransistor were achieved ranging from -30 to 30 V, which present channel conductance tuning by controlling the amplitude of gate bias. In addition, the gate-tunable synaptic plasticities (i.e., long-term potentiation (LTP) and long-term depression (LTD)) were obtained by changing the amplitude of gate bias from 10.0 to 13.5 V at an incremental of 0.5 V, exhibiting exponential growth of maximum channel conductance depending on the amplitude of gate bias. Finally, we demonstrated the fast training of the hardware-based deep neural network simulation using the gate-tunable synaptic plasticity of the designed memtransistor. The mechanism of single-gated memtransistor having quantum well memory nodes via Au nanoparticles and its application will be presented in detail. Acknowledgement This work was supported by the National Research Foundation of Korea(NRF) grant funded by the Korea government(MSIT) (No. RS-2023-00260527) and Institute of Information & communications Technology Planning & Evaluation (IITP) under the artificial intelligence semiconductor support program to nurture the best talents (IITP-(2023)-RS-2023-00253914) grant funded by the Korea government(MSIT)" References Fuller, E. J. et al. Parallel programming of an ionic floating-gate memory array for scalable neuromorphic computing. Science (80-. ). 364, 570–574 (2019).Yoon, J., Chang, M. & Khwa, W. Compute-in-Memory RRAM Macro With Write Verification and Multi-Bit Encoding. Jssc 57, 1–13 (2022).Kim, H. J. et al. Super-Linear-Threshold-Switching Selector with Multiple Jar-Shaped Cu-Filaments in the Amorphous Ge3Se7 Resistive Switching Layer in a Cross-Point Synaptic Memristor Array. Adv. Mater. 2203643, (2022).Lee, H. S. et al. Dual-Gated MoS2 Memtransistor Crossbar Array. Adv. Funct. Mater. 30, 1–12 (2020).Ding, G. et al. Reconfigurable 2D WSe2-Based Memtransistor for Mimicking Homosynaptic and Heterosynaptic Plasticity. Small 17, 1–13 (2021).Rehman, S., Khan, M. F., Kim, H. D. & Kim, S. Analog–digital hybrid computing with SnS2 memtransistor for low-powered sensor fusion. Nat. Commun. 13, 1–8 (2022). Figure 1

Cortical Tagged Synaptic Long-Term Depression in the Anterior Cingulate Cortex of Adult Mice.

The anterior cingulate cortex (ACC) is a key cortical region for pain perception and emotion. Different forms of synaptic plasticity, including long-term potentiation (LTP) and long-term depression (LTD), have been reported in the ACC. Synaptic tagging of LTP plays an important role in hippocampus-related associative memory. In this study, we demonstrate that synaptic tagging of LTD is detected in the ACC of adult male and female mice. This form of tagged LTD requires the activation of metabotropic glutamate receptor subtype 1 (mGluR1). The induction of tagged LTD is time-related with the strongest tagged LTD appearing when the interval between two independent stimuli is 30 min. Inhibitors of mGluR1 blocked the induction of tagged LTD; however, blocking N-methyl-d-aspartate receptors did not affect the induction of tagged LTD. Nimodipine, an inhibitor of L-type voltage-gated calcium channels, also blocked tagged LTD. In an animal model of amputation, we found that tagged LTD was either reduced or completely blocked. Together with our previous report of tagged LTP in the ACC, this study strongly suggests that excitatory synapses in the adult ACC are highly plastic. The biphasic tagging of synaptic transmission provides a new form of heterosynaptic plasticity in the ACC which has functional and pathophysiological significance in phantom pain.

Spatial interactions impact on Ca-driven synaptic plasticity: An ionic cable theory perspective

We extend our previous paper on deriving an approximate analytical solution of a nonlinear cable equation by including other ion channels in neurons and calcium dynamics based on reaction-diffusion dynamics that lead to a system of nonlinear cable equations. Here, excitable dendrite possesses clusters of voltage-activated ion channels that are discretely distributed as point sources or hotspots of transmembrane current along a continuous cable structure of fixed length. Single and/or trains of action potentials and spatially distributed synaptic inputs drive the depolarisation and activate sparsely distributed voltage-dependent calcium channels. This leads to calcium influx and diffusion in the cable. Here, time-dependent analytical solutions were obtained by applying a perturbation expansion of the non-dimensional voltage (Φ) and non-dimensional calcium (ΦCa) and then solving the resulting set of integral equations. We use this framework to gain insights into calcium-driven synaptic plasticity in dendrites. Many previous studies have traditionally focused on the local impact of calcium on whether the synapse's strength is increased (potentiated) or decreased (depressed). Only recently have studies focusing on heterosynaptic plasticity been gaining popularity, and here we ask the question of how a local plasticity rule is influenced by the spatially and temporally distributed synaptic inputs. Specifically, we focus on how synaptic inputs and calcium influx impact a calcium-derived temporal learning window for spike-timing-dependent plasticity (STDP) at nearby sites to assess the nature of the resulting distance-dependent interaction on the associated learning window at the synapse of interest.

Heterogeneous ion-modulated 2D-WS2 heterosynaptic memtransistor for controllable synaptic modulation and energy-efficient neuromorphic computing

Heterosynaptic plasticity plays a key role in addressing the interactions between local and global neuromodulation and the implementation of more complex biological functions. However, conventional heterosynaptic devices suffer from high energy consumption, high operating voltages and a lack of multi-modal regulation, which hinder the development of next-generation neuromorphic computing. Here, we report a heterogeneous ion-modulated 2D-WS2 four-terminal heterosynaptic memtransistor (Na+@WSHMT) with typical heterosynaptic plasticity at low stimulation voltage (200 mV) and ultra-low energy consumption (150 aJ). Moreover, the potential of four-terminal heterosynaptic memtransistors is demonstrated for enhancing the digit recognition with an increased recognition accuracy from 90.5 % to 93.3 % by stimulating the heterosynaptic terminal (light). Furthermore, convolutional image processing such as feature extraction is successfully performed by a convolutional neural network based on the multi-conductance characteristic of Na+@WSHMT. The ion-modulated heterosynaptic memtransistor provide a promising strategy for energy-efficient and controllable neuromorphic computing.

Computational Study on Interlocked-Ferroelectricity-Contributed High-Performance Memristors Based on Two-Dimensional van der Waals Ferroelectric Semiconductors.

In order to realize the prevailing artificial intelligence technology, memristor-implemented in-memory or neuromorphic computing is highly expected to break the bottleneck of von Neumann computers. Although high-performance memristors have been vigorously developed in labs or in industry, systematic computational investigations on memristors are seldom. Hence, it is urgent to provide theoretical or computational support for the exploration of memristor operating mechanisms or the screening of memristor materials. Here, a computational method based on the main input parameters learned from the first-principles calculations was developed to measure resistance switching of two-terminal memristors with sandwiched metal/ferroelectric semiconductor/metal architectures, which strikingly agrees with the experimental measurements. Based on our developed method, the diverse multiterminal memristors were designed to fully exploit the application of interlocked ferroelectricity of a ferroelectric semiconductor and realize their heterosynaptic plasticity, and their heterosynaptic behaviors can still be well described. Our developed method can provide a paradigm for the emulation of ferroelectric memristors and inspire subsequent computational exploration. Furthermore, our study also supplies a device optimization strategy based on the interlocked ferroelectricity and easy processing of two-dimensional van der Waals ferroelectric semiconductors, and our proposed heterosynaptic memristors still await further experimental exploration.

Plasticity of Response Properties of Mouse Visual Cortex Neurons Induced by Optogenetic Tetanization In Vivo.

Heterosynaptic plasticity, along with Hebbian homosynaptic plasticity, is an important mechanism ensuring the stable operation of learning neuronal networks. However, whether heterosynaptic plasticity occurs in the whole brain in vivo, and what role(s) in brain function in vivo it could play, remains unclear. Here, we used an optogenetics approach to apply a model of intracellular tetanization, which was established and employed to study heterosynaptic plasticity in brain slices, to study the plasticity of response properties of neurons in the mouse visual cortex in vivo. We show that optogenetically evoked high-frequency bursts of action potentials (optogenetic tetanization) in the principal neurons of the visual cortex induce long-term changes in the responses to visual stimuli. Optogenetic tetanization had distinct effects on responses to different stimuli, as follows: responses to optimal and orthogonal orientations decreased, responses to null direction did not change, and responses to oblique orientations increased. As a result, direction selectivity of the neurons decreased and orientation tuning became broader. Since optogenetic tetanization was a postsynaptic protocol, applied in the absence of sensory stimulation, and, thus, without association of presynaptic activity with bursts of action potentials, the observed changes were mediated by mechanisms of heterosynaptic plasticity. We conclude that heterosynaptic plasticity can be induced in vivo and propose that it may play important homeostatic roles in operation of neural networks by helping to prevent runaway dynamics of responses to visual stimuli and to keep the tuning of neuronal responses within the range optimized for the encoding of multiple features in population activity.

Heterosynaptic plasticity of the visuo-auditory projection requires cholecystokinin released from entorhinal cortex afferents.

The entorhinal cortex is involved in establishing enduring visuo-auditory associative memory in the neocortex. Here we explored the mechanisms underlying this synaptic plasticity related to projections from the visual and entorhinal cortices to the auditory cortex in mice using optogenetics of dual pathways. High-frequency laser stimulation (HFS laser) of the visuo-auditory projection did not induce long-term potentiation. However, after pairing with sound stimulus, the visuo-auditory inputs were potentiated following either infusion of cholecystokinin (CCK) or HFS laser of the entorhino-auditory CCK-expressing projection. Combining retrograde tracing and RNAscope in situ hybridization, we show that Cck expression is higher in entorhinal cortex neurons projecting to the auditory cortex than in those originating from the visual cortex. In the presence of CCK, potentiation in the neocortex occurred when the presynaptic input arrived 200 ms before postsynaptic firing, even after just five trials of pairing. Behaviorally, inactivation of the CCK+ projection from the entorhinal cortex to the auditory cortex blocked the formation of visuo-auditory associative memory. Our results indicate that neocortical visuo-auditory association is formed through heterosynaptic plasticity, which depends on release of CCK in the neocortex mostly from entorhinal afferents.

Cdc42 activation is necessary for heterosynaptic cooperation and competition

Synapses change their weights in response to neuronal activity and in turn, neuronal networks alter their response properties and ultimately allow the brain to store information as memories. As for memories, not all events are maintained over time. Maintenance of synaptic plasticity depends on the interplay between functional changes at synapses and the synthesis of plasticity-related proteins that are involved in stabilizing the initial functional changes. Different forms of synaptic plasticity coexist in time and across the neuronal dendritic area. Thus, homosynaptic plasticity refers to activity-dependent synaptic modifications that are input-specific, whereas heterosynaptic plasticity relates to changes in non-activated synapses. Heterosynaptic forms of plasticity, such as synaptic cooperation and competition allow neurons to integrate events that occur separated by relatively large time windows, up to one hour. Here, we show that activation of Cdc42, a Rho GTPase that regulates actin cytoskeleton dynamics, is necessary for the maintenance of long-term potentiation (LTP) in a time-dependent manner. Inhibiting Cdc42 activation does not alter the time-course of LTP induction and its initial expression but blocks its late maintenance. We show that Cdc42 activation is involved in the phosphorylation of cofilin, a protein involved in modulating actin filaments and that weak and strong synaptic activation leads to similar levels on cofilin phosphorylation, despite different levels of LTP expression. We show that Cdc42 activation is required for synapses to interact by cooperation or competition, supporting the hypothesis that modulation of the actin cytoskeleton provides an activity-dependent and time-restricted permissive state of synapses allowing synaptic plasticity to occur. We found that under competition, the sequence in which synapses are activated determines the degree of LTP destabilization, demonstrating that competition is an active destabilization process. Taken together, we show that modulation of actin cytoskeleton by Cdc42 activation is necessary for the expression of homosynaptic and heterosynaptic forms of plasticity. Determining the temporal and spatial rules that determine whether synapses cooperate or compete will allow us to understand how memories are associated.

Heterosynaptic plasticity in memristive and memcapacitive lipid bilayers: A snapshot review

Heterosynaptic plasticity in memristive and memcapacitive lipid bilayers: A snapshot review

A dynamic attractor network model of memory formation, reinforcement and forgetting.

Empirical evidence shows that memories that are frequently revisited are easy to recall, and that familiar items involve larger hippocampal representations than less familiar ones. In line with these observations, here we develop a modelling approach to provide a mechanistic understanding of how hippocampal neural assemblies evolve differently, depending on the frequency of presentation of the stimuli. For this, we added an online Hebbian learning rule, background firing activity, neural adaptation and heterosynaptic plasticity to a rate attractor network model, thus creating dynamic memory representations that can persist, increase or fade according to the frequency of presentation of the corresponding memory patterns. Specifically, we show that a dynamic interplay between Hebbian learning and background firing activity can explain the relationship between the memory assembly sizes and their frequency of stimulation. Frequently stimulated assemblies increase their size independently from each other (i.e. creating orthogonal representations that do not share neurons, thus avoiding interference). Importantly, connections between neurons of assemblies that are not further stimulated become labile so that these neurons can be recruited by other assemblies, providing a neuronal mechanism of forgetting.

Role of heterosynaptic plasticity in the modification of sensory responses of mouse visual cortex neurons

Role of heterosynaptic plasticity in the modification of sensory responses of mouse visual cortex neurons

Homosynaptic plasticity induction causes heterosynaptic changes at the unstimulated neighbors in an induction pattern and location-specific manner.

Dendritic spines are highly dynamic structures whose structural and functional fluctuations depend on multiple factors. Changes in synaptic strength are not limited to synapses directly involved in specific activity patterns. Unstimulated clusters of neighboring spines in and around the site of stimulation can also undergo alterations in strength. Usually, when plasticity is induced at single dendritic spines with glutamate uncaging, neighboring spines do not show any significant structural fluctuations. Here, using two-photon imaging and glutamate uncaging at single dendritic spines of hippocampal pyramidal neurons, we show that structural modifications at unstimulated neighboring spines occur and are a function of the temporal pattern of the plasticity-inducing stimulus. Further, the relative location of the unstimulated neighbors within the local dendritic segment correlates with the extent of heterosynaptic plasticity that is observed. These findings indicate that naturalistic patterns of activity at single spines can shape plasticity at nearby clusters of synapses, and may play a role in priming local inputs for further modifications.

Bio-inspired artificial heterosynapse based on carbon nanotubes memtransistor with dynamically tunable analog switching behavior

The swift advancement of artificial intelligence necessitates the exigency for a proficient information processing system. Taking inspiration from the intricate synapses of the human brain, we have crafted an artificial heterosynapse utilizing carbon nanotube (CNT) memtransistors. The multi-terminal heterosynaptic plasticity of CNTs memtransistor could be effectively modulated by gate voltage or drain voltage, which resembles the biological synapses affected by external neuromodulators. The artificial synapse skillfully replicates neuromorphic functionalities in response to pulse stimuli. This enables tunable analog switching behavior, multiple memory states, and complex neuromorphic learning. Furthermore, the Pavlovian classical conditioning experiments were conducted utilizing the synaptic device to achieve associative learning. The introduction of the CNTs memtransistor will propel the advancement of neuromorphic device technology and unlock novel opportunities for designing learning schemes with an additional degree of freedom.

Skewed distribution of spines is independent of presynaptic transmitter release and synaptic plasticity, and emerges early during adult neurogenesis.

Dendritic spines are crucial for excitatory synaptic transmission as the size of a spine head correlates with the strength of its synapse. The distribution of spine head sizes follows a lognormal-like distribution with more small spines than large ones. We analysed the impact of synaptic activity and plasticity on the spine size distribution in adult-born hippocampal granule cells from rats with induced homo- and heterosynaptic long-term plasticity in vivo and CA1 pyramidal cells from Munc13-1/Munc13-2 knockout mice with completely blocked synaptic transmission. Neither the induction of extrinsic synaptic plasticity nor the blockage of presynaptic activity degrades the lognormal-like distribution but changes its mean, variance and skewness. The skewed distribution develops early in the life of the neuron. Our findings and their computational modelling support the idea that intrinsic synaptic plasticity is sufficient for the generation, while a combination of intrinsic and extrinsic synaptic plasticity maintains lognormal-like distribution of spines.

Heterosynaptic Plasticity in a Vertical Two-Terminal Synaptic Device.

Vertical two-terminal synaptic devices based on resistive switching have shown great potential for emulating biological signal processing and implementing artificial intelligence learning circuitries. To mimic heterosynaptic behaviors in vertical two-terminal synaptic devices, an additional terminal is required for neuromodulator activity. However, adding an extra terminal, such as a gate of the field-effect transistor, may lead to low scalability. In this study, a vertical two-terminal Pt/bilayer Sr1.8Ag0.2Nb3O10 (SANO) nanosheet/Nb:SrTiO3 (Nb:STO) device emulates heterosynaptic plasticity by controlling the number of trap sites in the SANO nanosheet via modulation of the tunneling current. Similar to biological neuromodulation, we modulated the synaptic plasticity, pulsed pair facilitation, and cutoff frequency of a simple two-terminal device. Therefore, our synaptic device can add high-level learning such as associative learning to a neuromorphic system with a simple cross-bar array structure.

Asymmetric Voltage Attenuation in Dendrites Can Enable Hierarchical Heterosynaptic Plasticity.

Long-term synaptic plasticity is mediated via cytosolic calcium concentrations ([Ca2+]). Using a synaptic model that implements calcium-based long-term plasticity via two sources of Ca2+ - NMDA receptors and voltage-gated calcium channels (VGCCs) - we show in dendritic cable simulations that the interplay between these two calcium sources can result in a diverse array of heterosynaptic effects. When spatially clustered synaptic input produces a local NMDA spike, the resulting dendritic depolarization can activate VGCCs at nonactivated spines, resulting in heterosynaptic plasticity. NMDA spike activation at a given dendritic location will tend to depolarize dendritic regions that are located distally to the input site more than dendritic sites that are proximal to it. This asymmetry can produce a hierarchical effect in branching dendrites, where an NMDA spike at a proximal branch can induce heterosynaptic plasticity primarily at branches that are distal to it. We also explored how simultaneously activated synaptic clusters located at different dendritic locations synergistically affect the plasticity at the active synapses, as well as the heterosynaptic plasticity of an inactive synapse "sandwiched" between them. We conclude that the inherent electrical asymmetry of dendritic trees enables sophisticated schemes for spatially targeted supervision of heterosynaptic plasticity.

Astrocyte Calcium Signaling Shifts the Polarity of Presynaptic Plasticity

Astrocytes have been increasingly acknowledged to play active roles in regulating synaptic transmission and plasticity. Through a variety of metabotropic and ionotropic receptors expressed on their surface, astrocytes detect extracellular neurotransmitters, and in turn, release gliotransmitters to modify synaptic strength, while they can also alter neuronal membrane excitability by modulating extracellular ionic milieu. Given the seemingly large repertoire of synaptic modulation, when, where and how astrocytes interact with synapses remain to be fully understood. Previously, we have identified a role for astrocyte NMDA receptor and L-VGCCs signaling in heterosynaptic presynaptic plasticity and promoting the heterogeneity of presynaptic strengths at hippocampal synapses. Here, we have sought to further clarify the mode by which astrocytes regulate presynaptic plasticity by exploiting a reduced culture system to globally evoke NMDA receptor-dependent presynaptic plasticity. Recording from a postsynaptic neuron intracellularly loaded with BAPTA, briefly bath applying NMDA and glycine induces a stable decrease in the rate of spontaneous glutamate release, which requires the presence of astrocytes and the activation of A1 adenosine receptors. Upon preventing astrocyte calcium signaling or blocking L-VGCCs, NMDA + glycine application triggers an increase, rather than a decrease, in the rate of spontaneous glutamate release, thereby shifting the presynaptic plasticity to promote an increase in strength. Our findings point to a crucial and surprising role of astrocytes in controlling the polarity of NMDA receptor and adenosine-dependent presynaptic plasticity. Such a pivotal mechanism unveils the power of astrocytes in regulating computations performed by neural circuits and is expected to profoundly impact cognitive processes.

Two-dimensional interfacial diffusion model of inhibitory synaptic receptor dynamics

The diffusion-trapping of protein receptors in post-synaptic regions of a neuron’s plasma membrane plays a key role in determining the strength of synaptic connections and their regulation during learning and memory. In this paper, we construct and analyse a two-dimensional interfacial diffusion model of inhibitory synaptic receptor dynamics. The model involves three major components. First, the boundary of each synapse is treated as a semi-permeable interface due to the effects of cytoskeletal structures. Second, the effective diffusivity within a synapse is taken to be smaller than the extrasynaptic diffusivity due to the temporary binding to scaffold protein buffers within the synapse. Third, receptors from intracellular pools are inserted into the membrane extrasynaptically and internalized extrasynaptically and synaptically. We first solve the model equations for a single synapse in an unbounded domain and explore how the non-equilibrium steady-state number of synaptic receptors depends on model parameters including synaptic radius and the permeability of the synaptic interface. We then use matched asymptotic analysis to solve the corresponding problem of multiple synapses in a large, bounded domain. In particular, we show how diffusion mediates pairwise synaptic interactions that could provide a substrate for heterosynaptic plasticity. Finally, we indicate how to apply the model to the stochastic dynamics of single receptors.

Tribo‐ferro‐optoelectronic neuromorphic transistor of α‐In2Se3

AbstractInspired by biological neural networks, the fabrication of artificial neuromorphic systems with multimodal perception capacity shows promises in overcoming the “von Neumann bottleneck” and takes advantage of the efficient perception and computation of diverse types of signals. Here, we combine a triboelectric nanogenerator with an α‐phase indium selenide (α‐In2Se3) optoelectronic synaptic transistor to construct a tribo‐ferro‐optoelectronic artificial neuromorphic device with multimodal plasticity. Based on the excellent ferroelectric and optoelectronic characteristics of the α‐In2Se3 channel, typical synaptic behaviors (e.g., pair‐pulse facilitation and short‐term/long‐term plasticity) are successfully simulated in response to the synergistic effect of mechanical and optical stimuli. The interaction of mechanical displacement and light illumination enables heterosynaptic plasticity and spatiotemporal dynamic logic. Furthermore, multiple Boolean logical functions and associative learning behaviors are successfully implemented using the paired stimuli of displacement pulses and light pulses. The proposed tribo‐ferro‐optoelectronic artificial neuromorphic devices have great potential for application in interactive neural networks and next‐generation artificial intelligence.