Short-term synaptic plasticity

Aqueous chemimemristor based on proton-permeable graphene membranes

Memristive devices, electrical elements whose resistance depends on the history of applied electrical signals, are leading candidates for future data storage and neuromorphic computing. Memristive devices typically rely on solid-state technology, while aqueous memristive devices are crucial for biology-related applications such as next-generation brain-machine interfaces. Here, we report a simple graphene-based aqueous memristive device with long-term and tunable memory regulated by reversible voltage-induced interfacial acid-base equilibria enabled by selective proton permeation through the graphene. Surface-specific vibrational spectroscopy verifies that the memory of the graphene resistivity arises from the hysteretic proton permeation through the graphene, apparent from the reorganization of interfacial water at the graphene/water interface. The proton permeation alters the surface charge density on the CaF2 substrate of the graphene, affecting graphene's electron mobility, and giving rise to synapse-like resistivity dynamics. The results pave the way for developing experimentally straightforward and conceptually simple aqueous electrolyte-based neuromorphic iontronics using two-dimensional (2D) materials.

Optoelectronic Synapses Based on MXene/Violet Phosphorus van der Waals Heterojunctions for Visual-Olfactory Crossmodal Perception

The crossmodal interaction of different senses, which is an important basis for learning and memory in the human brain, is highly desired to be mimicked at the device level for developing neuromorphic crossmodal perception, but related researches are scarce. Here, we demonstrate an optoelectronic synapse for vision-olfactory crossmodal perception based on MXene/violet phosphorus (VP) van der Waals heterojunctions. Benefiting from the efficient separation and transport of photogenerated carriers facilitated by conductive MXene, the photoelectric responsivity of VP is dramatically enhanced by 7 orders of magnitude, reaching up to 7.7 A W-1. Excited by ultraviolet light, multiple synaptic functions, including excitatory postsynaptic currents, paired-pulse facilitation, short/long-term plasticity and "learning-experience" behavior, were demonstrated with a low power consumption. Furthermore, the proposed optoelectronic synapse exhibits distinct synaptic behaviors in different gas environments, enabling it to simulate the interaction of visual and olfactory information for crossmodal perception. This work demonstrates the great potential of VP in optoelectronics and provides a promising platform for applications such as virtual reality and neurorobotics.

A role for MCH neuron firing in modulating hippocampal plasticity threshold

It has been revealed that hypothalamic neurons containing the peptide, melanin-concentrating hormone (MCH) can influence learning [1] and memory formation [2], but the cellular mechanisms by which they perform this function are not well understood. Here, we examine the role of MCH neural input to the hippocampus, and show in vitro that optogenetically increasing MCH axon activity facilitates hippocampal plasticity by lowering the threshold for synaptic potentiation. These results align with increasing evidence that MCH neurons play a regulatory role in learning, and reveal that this could be achieved by modulating plasticity thresholds in the hippocampus.

Exploiting nonlinear dendritic adaptive computation in training deep Spiking Neural Networks

Inspired by the information transmission process in the brain, Spiking Neural Networks (SNNs) have gained considerable attention due to their event-driven nature. However, as the network structure grows complex, managing the spiking behavior within the network becomes challenging. Networks with excessively dense or sparse spikes fail to transmit sufficient information, inhibiting SNNs from exhibiting superior performance. Current SNNs linearly sum presynaptic information in postsynaptic neurons, overlooking the adaptive adjustment effect of dendrites on information processing. In this study, we introduce the Dendritic Spatial Gating Module (DSGM), which scales and translates the input, reducing the loss incurred when transforming the continuous membrane potential into discrete spikes. Simultaneously, by implementing the Dendritic Temporal Adjust Module (DTAM), dendrites assign different importance to inputs of different time steps, facilitating the establishment of the temporal dependency of spiking neurons and effectively integrating multi-step time information. The fusion of these two modules results in a more balanced spike representation within the network, significantly enhancing the neural network's performance. This approach has achieved state-of-the-art performance on static image datasets, including CIFAR10 and CIFAR100, as well as event datasets like DVS-CIFAR10, DVS-Gesture, and N-Caltech101. It also demonstrates competitive performance compared to the current state-of-the-art on the ImageNet dataset.

Hierarchies in Visual Pathway: Functions and Inspired Artificial Vision

The development of artificial intelligence has posed a challenge to machine vision based on conventional complementary metal-oxide semiconductor (CMOS) circuits owing to its high latency and inefficient power consumption originating from the data shuffling between memory and computation units. Gaining more insights into the function of every part of the visual pathway for visual perception can bring the capabilities of machine vision in terms of robustness and generality. Hardware acceleration of more energy-efficient and biorealistic artificial vision highly necessitates neuromorphic devices and circuits that are able to mimic the function of each part of the visual pathway. In this paper, we review the structure and function of the entire class of visual neurons from the retina to the primate visual cortex within reach (Chapter 2) are reviewed. Based on the extraction of biological principles, the recent hardware-implemented visual neurons located in different parts of the visual pathway are discussed in detail in Chapters 3 and 4. Furthermore, valuable applications of inspired artificial vision in different scenarios (Chapter 5) are provided. The functional description of the visual pathway and its inspired neuromorphic devices/circuits are expected to provide valuable insights for the design of next-generation artificial visual perception systems.

Tdrd3-null mice show post-transcriptional and behavioral impairments associated with neurogenesis and synaptic plasticity

The Topoisomerase 3B (Top3b) - Tudor domain containing 3 (Tdrd3) protein complex is the only dual-activity topoisomerase complex that can alter both DNA and RNA topology in animals. TOP3B mutations in humans are associated with schizophrenia, autism and cognitive disorders; and Top3b-null mice exhibit several phenotypes observed in animal models of psychiatric and cognitive disorders, including impaired cognitive and emotional behaviors, aberrant neurogenesis and synaptic plasticity, and transcriptional defects. Similarly, human TDRD3 genomic variants have been associated with schizophrenia, verbal short-term memory and educational attainment. However, the importance of Tdrd3 in normal brain function has not been examined in animal models. Here we generated a Tdrd3-null mouse strain and demonstrate that these mice display both shared and unique defects when compared to Top3b-null mice. Shared defects were observed in cognitive behaviors, synaptic plasticity, adult neurogenesis, newborn neuron morphology, and neuronal activity-dependent transcription; whereas defects unique to Tdrd3-deficient mice include hyperactivity, changes in anxiety-like behaviors, olfaction, increased new neuron complexity, and reduced myelination. Interestingly, multiple genes critical for neurodevelopment and cognitive function exhibit reduced levels in mature but not nascent transcripts. We infer that the entire Top3b-Tdrd3 complex is essential for normal brain function, and that defective post-transcriptional regulation could contribute to cognitive and psychiatric disorders.

Coexisting Phases in Transition Metal Dichalcogenides: Overview, Synthesis, Applications, and Prospects

Over the past decade, significant advancements have been made in phase engineering of two-dimensional transition metal dichalcogenides (TMDCs), thereby allowing controlled synthesis of various phases of TMDCs and facile conversion between them. Recently, there has been emerging interest in TMDC coexisting phases, which contain multiple phases within one nanostructured TMDC. By taking advantage of the merits from the component phases, the coexisting phases offer enhanced performance in many aspects compared with single-phase TMDCs. Herein, this review article thoroughly expounds the latest progress and ongoing efforts on the syntheses, properties, and applications of TMDC coexisting phases. The introduction section overviews the main phases of TMDCs (2H, 3R, 1T, 1T', 1Td), along with the advantages of phase coexistence. The subsequent section focuses on the synthesis methods for coexisting phases of TMDCs, with particular attention to local patterning and random formations. Furthermore, on the basis of the versatile properties of TMDC coexisting phases, their applications in magnetism, valleytronics, field-effect transistors, memristors, and catalysis are discussed. Lastly, a perspective is presented on the future development, challenges, and potential opportunities of TMDC coexisting phases. This review aims to provide insights into the phase engineering of 2D materials for both scientific and engineering communities and contribute to further advancements in this emerging field.

Measuring excitation-inhibition balance through spectral components of local field potentials

The balance between excitation and inhibition is critical to brain functioning, and dysregulation of this balance is a hallmark of numerous psychiatric conditions. Measuring this excitation-inhibition (E:I) balance in vivo has remained difficult, but theoretical models have proposed that characteristics of local field potentials (LFP) may provide an accurate proxy. To establish a conclusive link between LFP and E:I balance, we recorded single units and LFP from the prefrontal cortex (mPFC) of rats during decision making. Dynamic measures of synaptic coupling strength facilitated direct quantification of E:I balance and revealed a strong inverse relationship to broadband spectral power of LFP. These results provide a critical link between LFP and underlying network properties, opening the door for non-invasive recordings to measure E:I balance in clinical settings.

Morphological and functional alterations of neuromuscular synapses in a mouse model of ACTA1 congenital myopathy

Mutations in skeletal muscle α-actin (Acta1) cause myopathies. In a mouse model of congenital myopathy, heterozygous Acta1 (H40Y) knock-in (Acta1+/Ki) mice exhibit features of human nemaline myopathy, including premature lethality, severe muscle weakness, reduced mobility, and the presence of nemaline rods in muscle fibers. In this study, we investigated the impact of Acta1 (H40Y) mutation on the neuromuscular junction (NMJ). We found that the NMJs were markedly fragmented in Acta1+/Ki mice. Electrophysiological analysis revealed a decrease in amplitude but increase in frequency of miniature end-plate potential (mEPP) at the NMJs in Acta1+/Ki mice, compared with those in wild type (Acta1+/+) mice. Evoked end-plate potential (EPP) remained similar at the NMJs in Acta1+/Ki and Acta1+/+ mice, but quantal content was increased at the NMJs in Acta1+/Ki, compared with Acta1+/+ mice, suggesting a homeostatic compensation at the NMJs in Acta1+/Ki mice to maintain normal levels of neurotransmitter release. Furthermore, short-term synaptic plasticity of the NMJs was compromised in Acta1+/Ki mice. Together, these results demonstrate that skeletal Acta1 H40Y mutation, albeit muscle-origin, leads to both morphological and functional defects at the NMJ.

Synaptic Plasticity Modulation of Neuromorphic Transistors through Phosphorus Concentration in Phosphosilicate Glass Electrolyte Gate

This study proposes a phosphosilicate glass (PSG)-based electrolyte gate synaptic transistor with varying phosphorus (P) concentrations. A metal oxide semiconductor capacitor structure device was employed to measure the frequency-dependent (C-f) capacitance curve, demonstrating that the PSG electric double-layer capacitance increased at 103 Hz with rising P concentration. Fourier transform infrared spectroscopy spectra analysis facilitated a theoretical understanding of the C-f curve results, examining peak differences in the P-OH structure based on P concentration. Using the proposed synaptic transistors with different P concentrations, changes in the hysteresis window were investigated by measuring the double-sweep transfer curves. Subsequently, alterations in proton movement within the PSG and charge characteristics at the channel/PSG electrolyte interface were observed through excitatory post-synaptic currents, paired-pulse facilitation, signal-filtering functions, resting current levels, and potentiation and depression characteristics. Finally, we demonstrated the proposed neuromorphic system's feasibility based on P concentration using the Modified National Institute of Standards and Technology learning simulations. The study findings suggest that, by adjusting the PSG film's P concentration for the same electrical stimulus, it is possible to selectively mimic the synaptic signal strength of human synapses. Therefore, this approach can positively contribute to the implementation of various neuromorphic systems.

Experience shapes chandelier cell function and structure in the visual cortex

Detailed characterization of interneuron types in primary visual cortex (V1) has greatly contributed to understanding visual perception, yet the role of chandelier cells (ChCs) in visual processing remains poorly characterized. Using viral tracing we found that V1 ChCs predominantly receive monosynaptic input from local layer 5 pyramidal cells and higher-order cortical regions. Two-photon calcium imaging and convolutional neural network modeling revealed that ChCs are visually responsive but weakly selective for stimulus content. In mice running in a virtual tunnel, ChCs respond strongly to events known to elicit arousal, including locomotion and visuomotor mismatch. Repeated exposure of the mice to the virtual tunnel was accompanied by reduced visual responses of ChCs and structural plasticity of ChC boutons and axon initial segment length. Finally, ChCs only weakly inhibited pyramidal cells. These findings suggest that ChCs provide an arousal-related signal to layer 2/3 pyramidal cells that may modulate their activity and/or gate plasticity of their axon initial segments during behaviorally relevant events.

Enhancement of the Evoked Excitatory Transmission in the Nucleus Tractus Solitarius Neurons after Sustained Hypoxia in Mice Depends on A2A Receptors

The first synapses of the afferents of peripheral chemoreceptors are located in the Nucleus Tractus Solitarius (NTS) and there is evidence that short-term sustained hypoxia (SH - 24 h, FiO2 0.1) facilitates glutamatergic transmission in NTS neurons of rats. Adenosine is an important neuromodulator of synaptic transmission and hypoxia contributes to increase its extracellular concentration. The A2A receptors mediate the excitatory actions of adenosine and are active players in the modulation of neuronal networks in the NTS. Herein, we used knockout mice for A2A receptors (A2AKO) and electrophysiological recordings of NTS neurons were performed to evaluate the contribution of these receptors in the changes in synaptic transmission in NTS neurons of mice submitted to SH. The membrane passive properties and excitability of NTS neurons were not affected by SH and were similar between A2AKO and wild-type mice. The overall amplitude of spontaneous glutamatergic currents in NTS neurons of A2AKO mice was lower than in Balb/c WT mice. SH increased the amplitude of evoked glutamatergic currents of NTS neurons from WT mice by a non-presynaptic mechanism, but this enhancement was not observed in NTS neurons of A2AKO mice. Under normoxia, the amplitude of evoked glutamatergic currents was similar between WT and A2AKO mice. The data indicate that A2A receptors (a) modulate spontaneous glutamatergic currents, (b) do not modulate the evoked glutamatergic transmission in the NTS neurons under control conditions, and (c) are required for the enhancement of glutamatergic transmission observed in the NTS neurons of mice submitted to SH.

A maximum of two readily releasable vesicles per docking site at a cerebellar single active zone synapse

Recent research suggests that in central mammalian synapses, active zones contain several docking sites acting in parallel. Before release, one or several synaptic vesicles (SVs) are thought to bind to each docking site, forming the readily releasable pool (RRP). Determining the RRP size per docking site has important implications for short-term synaptic plasticity. Here, using mouse cerebellar slices, we take advantage of recently developed methods to count the number of released SVs at single glutamatergic synapses in response to trains of action potentials (APs). In each recording, the number of docking sites was determined by fitting with a binomial model the number of released SVs in response to individual APs. After normalization with respect to the number of docking sites, the summed number of released SVs following a train of APs was used to estimate of the RRP size per docking site. To improve this estimate, various steps were taken to maximize the release probability of docked SVs, the occupancy of docking sites, as well as the extent of synaptic depression. Under these conditions, the RRP size reached a maximum value close to two SVs per docking site. The results indicate that each docking site contains two distinct SV-binding sites that can simultaneously accommodate up to one SV each. They further suggest that under special experimental conditions, as both sites are close to full occupancy, a maximal RRP size of two SVs per docking site can be reached. More generally, the results validate a sequential two-step docking model previously proposed at this preparation.

Cyclic nucleotide-induced bidirectional long-term synaptic plasticity in Drosophila mushroom body

Activation of the cAMP pathway is one of the common mechanisms underlying long-term potentiation (LTP). In the Drosophila mushroom body, simultaneous activation of odor-coding Kenyon cells (KCs) and reinforcement-coding dopaminergic neurons activates adenylyl cyclase in KC presynaptic terminals, which is believed to trigger synaptic plasticity underlying olfactory associative learning. However, learning induces long-term depression (LTD) at these synapses, contradicting the universal role of cAMP as a facilitator of transmission. Here, we develop a system to electrophysiologically monitor both short-term and long-term synaptic plasticity at KC output synapses and demonstrate that they are indeed an exception where activation of the cAMP/protein kinase A pathway induces LTD. Contrary to the prevailing model, our cAMP imaging finds no evidence for synergistic action of dopamine and KC activity on cAMP synthesis. Furthermore, we find that forskolin-induced cAMP increase alone is insufficient for plasticity induction; it additionally requires simultaneous KC activation to replicate the presynaptic LTD induced by pairing with dopamine. On the other hand, activation of the cGMP pathway paired with KC activation induces slowly developing LTP, proving antagonistic actions of the two second-messenger pathways predicted by behavioral study. Finally, KC subtype-specific interrogation of synapses reveals that different KC subtypes exhibit distinct plasticity duration even among synapses on the same postsynaptic neuron. Thus, our work not only revises the role of cAMP in synaptic plasticity by uncovering the unexpected convergence point of the cAMP pathway and neuronal activity, but also establishes the methods to address physiological mechanisms of synaptic plasticity in this important model.

Short-term Hebbian learning can implement transformer-like attention

Transformers have revolutionized machine learning models of language and vision, but their connection with neuroscience remains tenuous. Built from attention layers, they require a mass comparison of queries and keys that is difficult to perform using traditional neural circuits. Here, we show that neurons can implement attention-like computations using short-term, Hebbian synaptic potentiation. We call our mechanism the match-and-control principle and it proposes that when activity in an axon is synchronous, or matched, with the somatic activity of a neuron that it synapses onto, the synapse can be briefly strongly potentiated, allowing the axon to take over, or control, the activity of the downstream neuron for a short time. In our scheme, the keys and queries are represented as spike trains and comparisons between the two are performed in individual spines allowing for hundreds of key comparisons per query and roughly as many keys and queries as there are neurons in the network.

Interpretation of presynaptic phenotypes of synaptic plasticity in terms of a two-step priming process

Studies on synaptic proteins involved in neurotransmitter release often aim at distinguishing between their roles in vesicle priming (the docking of synaptic vesicles to the plasma membrane and the assembly of a release machinery) as opposed to the process of vesicle fusion. This has traditionally been done by estimating two parameters, the size of the pool of fusion-competent vesicles (the readily releasable pool, RRP) and the probability that such vesicles are released by an action potential, with the aim of determining how these parameters are affected by molecular perturbations. Here, it is argued that the assumption of a homogeneous RRP may be too simplistic and may blur the distinction between vesicle priming and fusion. Rather, considering priming as a dynamic and reversible multistep process allows alternative interpretations of mutagenesis-induced changes in synaptic transmission and suggests mechanisms for variability in synaptic strength and short-term plasticity among synapses, as well as for interactions between short- and long-term plasticity. In many cases, assigned roles of proteins or causes for observed phenotypes are shifted from fusion- to priming-related when considering multistep priming. Activity-dependent enhancement of priming is an essential element in this alternative view and its variation among synapse types can explain why some synapses show depression and others show facilitation at low to intermediate stimulation frequencies. Multistep priming also suggests a mechanism for frequency invariance of steady-state release, which can be observed in some synapses involved in sensory processing.

Proteomic-Based Studies on Memory Formation in Normal and Neurodegenerative Disease-Affected Brains

A critical aspect of cognition is the ability to acquire, consolidate, and evoke memories, which is considerably impaired by neurodegenerative disorders such as Alzheimer's and Parkinson's diseases. These mnemonic processes are dependent on signaling cascades, which involve protein expression and degradation. Recent mass spectrometry (MS)-based proteomics has opened a range of possibilities for the study of memory formation and impairment, making it possible to research protein systems not studied before. However, in the context of synaptic proteome related to learning processes and memory formation, a deeper understanding of the synaptic proteome temporal dynamics after induction of synaptic plasticity and the molecular changes underlying the cognitive deficits seen in neurodegenerative diseases is needed. This review analyzes the applications of proteomics for understanding memory processes in both normal and neurodegenerative conditions. Moreover, the most critical experimental studies have been summarized using the PANTHER overrepresentation test. Finally, limitations associated with investigations of memory studies in physiological and neurodegenerative disorders have also been discussed.

Reliable synaptic plasticity of InGaZnO transistor with TiO2interlayer

We demonstrate an InGaZnO (IGZO)-based synaptic transistor with a TiO2buffer layer. The structure of the synaptic transistor with TiO2inserted between the Ti metal electrode and an IGZO semiconductor channel O2trapping layer produces a large hysteresis window, which is crucial for achieving synaptic functionality. The Ti/TiO2/IGZO synaptic transistor exhibits reliable synaptic plasticity features such as excitatory post-synaptic current, paired-pulse facilitation, and potentiation and depression, originating from the reversible charge trapping and detrapping in the TiO2layer. Finally, the pattern recognition accuracy of Modified National Institute of Standards and Technology handwritten digit images was modeled using CrossSim simulation software. The simulation results present a high image recognition accuracy of ∼89%. Therefore, this simple approach using an oxide buffer layer can aid the implementation of high-performance synaptic devices for neuromorphic computing systems.

Ultralow Energy Consumption Angstrom-Fluidic Memristor

The emergence of nanofluidic memristors has made a giant leap to mimic the neuromorphic functions of biological neurons. Here, we report neuromorphic signaling using Angstrom-scale funnel-shaped channels with poly-l-lysine (PLL) assembled at nano-openings. We found frequency-dependent current-voltage characteristics under sweeping voltage, which represents a diode in low frequencies, but it showed pinched current hysteresis as frequency increases. The current hysteresis is strongly dependent on pH values but weakly dependent on salt concentration. We attributed the current hysteresis to the entropy barrier of PLL molecules entering and exiting the Angstrom channels, resulting in reversible voltage-gated open-close state transitions. We successfully emulated the synaptic adaptation of Hebbian learning using voltage spikes and obtained a minimum energy consumption of 2-23 fJ in each spike per channel. Our findings pave a new way to mimic neuronal functions by Angstrom channels in low energy consumption.

Highly Reliable 3D Channel Memory and Its Application in a Neuromorphic Sensory System for Hand Gesture Recognition

Brain-inspired neuromorphic computing systems, based on a crossbar array of two-terminal multilevel resistive random-access memory (RRAM), have attracted attention as promising technologies for processing large amounts of unstructured data. However, the low reliability and inferior conductance tunability of RRAM, caused by uncontrollable metal filament formation in the uneven switching medium, result in lower accuracy compared to the software neural network (SW-NN). In this work, we present a highly reliable CoOx-based multilevel RRAM with an optimized crystal size and density in the switching medium, providing a three-dimensional (3D) grain boundary (GB) network. This design enhances the reliability of the RRAM by improving the cycle-to-cycle endurance and device-to-device stability of the I-V characteristics with minimal variation. Furthermore, the designed 3D GB-channel RRAM (3D GB-RRAM) exhibits excellent conductance tunability, demonstrating high symmetricity (624), low nonlinearity (βLTP/βLTD ∼ 0.20/0.39), and a large dynamic range (Gmax/Gmin ∼ 31.1). The cyclic stability of long-term potentiation and depression also exceeds 100 cycles (105 voltage pulses), and the relative standard deviation of Gmax/Gmin is only 2.9%. Leveraging these superior reliability and performance attributes, we propose a neuromorphic sensory system for finger motion tracking and hand gesture recognition as a potential elemental technology for the metaverse. This system consists of a stretchable double-layered photoacoustic strain sensor and a crossbar array neural network. We perform training and recognition tasks on ultrasonic patterns associated with finger motion and hand gestures, attaining a recognition accuracy of 97.9% and 97.4%, comparable to that of SW-NN (99.8% and 98.7%).

Artificial Neuron Devices

Efforts to design devices emulating complex cognitive abilities and response processes of biological systems have long been a coveted goal. Recent advancements in flexible electronics, mirroring human tissue's mechanical properties, hold significant promise. Artificial neuron devices, hinging on flexible artificial synapses, bioinspired sensors, and actuators, are meticulously engineered to mimic the biological systems. However, this field is in its infancy, requiring substantial groundwork to achieve autonomous systems with intelligent feedback, adaptability, and tangible problem-solving capabilities. This review provides a comprehensive overview of recent advancements in artificial neuron devices. It starts with fundamental principles of artificial synaptic devices and explores artificial sensory systems, integrating artificial synapses and bioinspired sensors to replicate all five human senses. A systematic presentation of artificial nervous systems follows, designed to emulate fundamental human nervous system functions. The review also discusses potential applications and outlines existing challenges, offering insights into future prospects. We aim for this review to illuminate the burgeoning field of artificial neuron devices, inspiring further innovation in this captivating area of research.

MoS2-Based Memristor: Robust Resistive Switching Behavior and Reliable Biological Synapse Emulation

Memristors are recognized as crucial devices for future nonvolatile memory and artificial intelligence. Due to their typical neuron-synapse-like metal-insulator-metal(MIM) sandwich structure, they are widely used to simulate biological synapses and have great potential in advancing biological synapse simulation. However, the high switch voltage and inferior stability of the memristor restrict the broader application to the emulation of the biological synapse. In this study, we report a vertically structured memristor based on few-layer MoS2. The device shows a lower switching voltage below 0.6 V, with a high ON/OFF current ratio of 104, good stability of more than 180 cycles, and a long retention time exceeding 3 × 103 s. In addition, the device has successfully simulated various biological synaptic functions, including potential/depression propagation, paired-pulse facilitation (PPF), and long-term potentiation/long-term depression (LTP/LTD) modulation. These results have significant implications for the design of a two-dimensional transition-metal dichalcogenides composite material memristor that aim to mimic biological synapses, representing promising avenues for the development of advanced neuromorphic computing systems.

Versatile Neuromorphic Modulation and Biosensing based on N-type Small-molecule Organic Mixed Ionic-Electronic Conductors

The ion/chemical-based modulation feature of organic mixed ionic-electronic conductors (OMIECs) are critical to advancing next generation bio-integrated neuromorphic hardware. Despite achievements with polymeric OMIECs in organic electrochemical neuronal synapse (OENS). However, small molecule OMIECs based OENS has not yet been realized. Here, for the first time, we demonstrate an effective materials design concept of combining n-type fused all-acceptor small molecule OMIECs with subtle side chain optimization that enables robustly and flexibly modulating versatile synaptic behavior and sensing neurotransmitter in solid or aqueous electrolyte, operating in accumulation modes. By judicious tuning the ending side chains, the linear oligoether and butyl chain derivative gNR-Bu exhibits higher recognition accuracy for a model artificial neural network (ANN) simulation, higher steady conductance states and more outstanding ambient stability, which is superior to the state-of-art n-type OMIECs based OENS. These superior artificial synapse characteristics of gNR-Bu can be attributed to its higher crystallinity with stronger ion bonding capacities. More impressively, we unprecedentedly realized n-type small-molecule OMIECs based OENS as a neuromorphic biosensor enabling to respond synaptic communication signals of dopamine even at sub-μM level in aqueous electrolyte. This work may open a new path of small-molecule ion-electron conductors for next-generation ANN and bioelectronics.

Small-molecule targeting AMPA-mediated excitotoxicity has therapeutic effects in mouse models for multiple sclerosis

While most research and treatments for multiple sclerosis (MS) focus on autoimmune reactions causing demyelination, it is possible that neurodegeneration precedes the autoimmune response. Hence, glutamate receptor antagonists preventing excitotoxicity showed promise in MS animal models, though blocking glutamate signaling prevents critical neuronal functions. This study reports the discovery of a small molecule that prevents AMPA-mediated excitotoxicity by targeting an allosteric binding site. A machine learning approach was used to screen for small molecules targeting the AMPA receptor GluA2 subunit. The lead candidate has potent effects in restoring neurological function and myelination while reducing the immune response in experimental autoimmune encephalitis and cuprizone MS mouse models without affecting basal neurotransmission or learning and memory. These findings facilitate development of a treatment for MS with a different mechanism of action than current immune modulatory drugs and avoids important off-target effects of glutamate receptor antagonists. This class of MS therapeutics could be useful as an alternative or complementary treatment to existing therapies.

Astrocytes control hippocampal synaptic plasticity through the vesicular-dependent release of D-serine

Astrocytes, the most abundant glial cells in the central nervous system (CNS), sense synaptic activity and respond through the release of gliotransmitters, a process mediated by intracellular Ca2+ level changes and SNARE-dependent mechanisms. Ionotropic N-methyl-D-aspartate (NMDA) receptors, which are activated by glutamate along with D-serine or glycine, play a crucial role in learning, memory, and synaptic plasticity. However, the precise impact of astrocyte-released D-serine on neuronal modulation remains insufficiently characterized. To address this, we have used the dominant negative SNARE (dnSNARE) mouse model, which selectively inhibits SNARE-dependent exocytosis from astrocytes. We recorded field excitatory postsynaptic potentials (fEPSPs) in CA3-CA1 synapses within hippocampal slices obtained from dnSNARE mice and wild-type (Wt) littermates. Our results demonstrate that hippocampal θ-burst long-term potentiation (LTP), a critical form of synaptic plasticity, is impaired in hippocampal slices from dnSNARE mice. Notably, this LTP impairment was rescued upon incubation with D-serine. To further investigate the involvement of astrocytes in D-serine-mediated mechanisms of LTP maintenance, we perfused hippocampal slices with L-serine - a substrate used by both neurons and astrocytes for D-serine production. The enhancement in LTP observed in dnSNARE mice was exclusively associated with D-serine presence, with no effects evident in the presence of L-serine. Additionally, both D- and L-serine reduced basal synaptic strength in the hippocampal slices of both Wt and dnSNARE mice. These results provide compelling evidence that distinct processes underlie the modulation of basal synaptic transmission and LTP through D-serine. Our findings underscore the pivotal contribution of astrocytes in D-serine-mediated processes that govern LTP establishment and basal transmission. This study not only provides essential insights into the intricate interplay between neurons and astrocytes but also emphasizes their collective role in shaping hippocampal synaptic function.

Heterosynaptic plasticity-induced modulation of synapses

Plasticity is a common feature of synapses that is stated in different ways and occurs through several mechanisms. The regular action of the brain needs to be balanced in several neuronal and synaptic features, one of which is synaptic plasticity. The different homeostatic processes, including the balance between excitation/inhibition or homeostasis of synaptic weights at the single-neuron level, may obtain this. Homosynaptic Hebbian-type plasticity causes associative alterations of synapses. Both homosynaptic and heterosynaptic plasticity characterize the corresponding aspects of adjustable synapses, and both are essential for the regular action of neural systems and their plastic synapses.In this review, we will compare homo- and heterosynaptic plasticity and the main factors affecting the direction of plastic changes. This review paper will also discuss the diverse functions of the different kinds of heterosynaptic plasticity and their properties. We argue that a complementary system of heterosynaptic plasticity demonstrates an essential cellular constituent for homeostatic modulation of synaptic weights and neuronal activity.

Interactions between specialized gain control mechanisms in olfactory processing

Gain control is a process that adjusts a system's sensitivity when input levels change. Neural systems contain multiple mechanisms of gain control, but we do not understand why so many mechanisms are needed or how they interact. Here, we investigate these questions in the Drosophila antennal lobe, where we identify several types of inhibitory interneurons with specialized gain control functions. We find that some interneurons are nonspiking, with compartmentalized calcium signals, and they specialize in intra-glomerular gain control. Conversely, we find that other interneurons are recruited by strong and widespread network input; they specialize in global presynaptic gain control. Using computational modeling and optogenetic perturbations, we show how these mechanisms can work together to improve stimulus discrimination while also minimizing temporal distortions in network activity. Our results demonstrate how the robustness of neural network function can be increased by interactions among diverse and specialized mechanisms of gain control.

Comparing the synaptic potentiation in schaffer collateral-CA1 synapses in dorsal and intermediate regions of the hippocampus in normal and kindled rats

There is growing evidence that the hippocampus comprises diverse neural circuits that exhibit longitudinal variation in their properties, however, the intermediate region of the hippocampus has received comparatively little attention. Therefore, this study was designed to compared short- and long-term synaptic plasticity between the dorsal and intermediate regions of the hippocampus in normal and PTZ-kindled rats. Short-term plasticity was assessed by measuring the ratio of field excitatory postsynaptic potentials' (fEPSPs) slope in response to paired-pulse stimulation at three different inter-pulse intervals (20, 80, and 160 ms), while long-term plasticity was assessed using primed burst stimulation (PBS). The results showed that the basal synaptic strength differed between the dorsal and intermediate regions of the hippocampus in both control and kindled rats. In the control group, paired-pulse stimulation of Schaffer collaterals resulted in a significantly lower fEPSP slope in the intermediate part of the hippocampus compared to the dorsal region. Additionally, the magnitude of long-term potentiation (LTP) was significantly lower in the intermediate part of the hippocampus compared to the dorsal region. In PTZ-kindled rats, both short-term facilitation and long-term potentiation were impaired in both regions of the hippocampus. Interestingly, there was no significant difference in synaptic plasticity between the dorsal and intermediate regions in PTZ-kindled rats, despite impairments in both regions. This suggests that seizures eliminate the regional difference between the dorsal and intermediate parts of the hippocampus, resulting in similar electrophysiological activity in both regions in kindled animals. Future studies should consider this when investigating the responses of the dorsal and intermediate regions of the hippocampus following PTZ kindling.

Silences, spikes and bursts: Three-part knot of the neural code

When a neuron breaks silence, it can emit action potentials in a number of patterns. Some responses are so sudden and intense that electrophysiologists felt the need to single them out, labelling action potentials emitted at a particularly high frequency with a metonym - bursts. Is there more to bursts than a figure of speech? After all, sudden bouts of high-frequency firing are expected to occur whenever inputs surge. The burst coding hypothesis advances that the neural code has three syllables: silences, spikes and bursts. We review evidence supporting this ternary code in terms of devoted mechanisms for burst generation, synaptic transmission and synaptic plasticity. We also review the learning and attention theories for which such a triad is beneficial.

Neuronal and synaptic adaptations underlying the benefits of deep brain stimulation for Parkinson's disease

Deep brain stimulation (DBS) is a well-established and effective treatment for patients with advanced Parkinson's disease (PD), yet its underlying mechanisms remain enigmatic. Optogenetics, primarily conducted in animal models, provides a unique approach that allows cell type- and projection-specific modulation that mirrors the frequency-dependent stimulus effects of DBS. Opto-DBS research in animal models plays a pivotal role in unraveling the neuronal and synaptic adaptations that contribute to the efficacy of DBS in PD treatment. DBS-induced neuronal responses rely on a complex interplay between the distributions of presynaptic inputs, frequency-dependent synaptic depression, and the intrinsic excitability of postsynaptic neurons. This orchestration leads to conversion of firing patterns, enabling both antidromic and orthodromic modulation of neural circuits. Understanding these mechanisms is vital for decoding position- and programming-dependent effects of DBS. Furthermore, patterned stimulation is emerging as a promising strategy yielding long-lasting therapeutic benefits. Research on the neuronal and synaptic adaptations to DBS may pave the way for the development of more enduring and precise modulation patterns. Advanced technologies, such as adaptive DBS or directional electrodes, can also be integrated for circuit-specific neuromodulation. These insights hold the potential to greatly improve the effectiveness of DBS and advance PD treatment to new levels.

Alterations in Rat Hippocampal Glutamatergic System Properties after Prolonged Febrile Seizures

Febrile seizures during early childhood may result in central nervous system developmental disorders. However, the specific mechanisms behind the impact of febrile seizures on the developing brain are not well understood. To address this gap in knowledge, we employed a hyperthermic model of febrile seizures in 10-day-old rats and tracked their development over two months. Our objective was to determine the degree to which the properties of the hippocampal glutamatergic system are modified. We analyzed whether pyramidal glutamatergic neurons in the hippocampus die after febrile seizures. Our findings indicate that there is a reduction in the number of neurons in various regions of the hippocampus in the first two days after seizures. The CA1 field showed the greatest susceptibility, and the reduction in the number of neurons in post-FS rats in this area appeared to be long-lasting. Electrophysiological studies indicate that febrile seizures cause a reduction in glutamatergic transmission, leading to decreased local field potential amplitude. This impairment could be attributable to diminished glutamate release probability as evidenced by decreases in the frequency of miniature excitatory postsynaptic currents and increases in the paired-pulse ratio of synaptic responses. We also found higher threshold current causing hind limb extension in the maximal electroshock seizure threshold test of rats 2 months after febrile seizures compared to the control animals. Our research suggests that febrile seizures can impair glutamatergic transmission, which may protect against future seizures.

Perinatal Depression and the Role of Synaptic Plasticity in Its Pathogenesis and Treatment

Emerging evidence indicates that synaptic plasticity is significantly involved in the pathophysiology and treatment of perinatal depression. Animal models have demonstrated the effects of overstimulated or weakened synapses in various circuits of the brain in causing affective disturbances. GABAergic theory of depression, stress, and the neuroplasticity model of depression indicate the role of synaptic plasticity in the pathogenesis of depression. Multiple factors related to perinatal depression like hormonal shifts, newer antidepressants, mood stabilizers, monoamine systems, biomarkers, neurotrophins, cytokines, psychotherapy and electroconvulsive therapy have demonstrated direct and indirect effects on synaptic plasticity. In this review, we discuss and summarize the various patho-physiology-related effects of synaptic plasticity in depression. We also discuss the association of treatment-related aspects related to psychotropics, electroconvulsive therapy, neuromodulation, psychotherapy, physical exercise and yoga with synaptic plasticity in perinatal depression. Future insights into newer methods of treatment directed towards the modulation of neuroplasticity for perinatal depression will be discussed.

Modulation of prefrontal couplings by prior belief-related responses in ventromedial prefrontal cortex

Humans and other animals can maintain constant payoffs in an uncertain environment by steadily re-evaluating and flexibly adjusting current strategy, which largely depends on the interactions between the prefrontal cortex (PFC) and mediodorsal thalamus (MD). While the ventromedial PFC (vmPFC) represents the level of uncertainty (i.e., prior belief about external states), it remains unclear how the brain recruits the PFC-MD network to re-evaluate decision strategy based on the uncertainty. Here, we leverage non-linear dynamic causal modeling on fMRI data to test how prior belief-dependent activity in vmPFC gates the information flow in the PFC-MD network when individuals switch their decision strategy. We show that the prior belief-related responses in vmPFC had a modulatory influence on the connections from dorsolateral PFC (dlPFC) to both, lateral orbitofrontal (lOFC) and MD. Bayesian parameter averaging revealed that only the connection from the dlPFC to lOFC surpassed the significant threshold, which indicates that the weaker the prior belief, the less was the inhibitory influence of the vmPFC on the strength of effective connections from dlPFC to lOFC. These findings suggest that the vmPFC acts as a gatekeeper for the recruitment of processing resources to re-evaluate the decision strategy in situations of high uncertainty.

Light-Stimulated IGZO Transistors with Tunable Synaptic Plasticity Based on Casein Electrolyte Electric Double Layer for Neuromorphic Systems

In this study, optoelectronic synaptic transistors based on indium-gallium-zinc oxide (IGZO) with a casein electrolyte-based electric double layer (EDL) were examined. The casein electrolyte played a crucial role in modulating synaptic plasticity through an internal proton-induced EDL effect. Thus, important synaptic behaviors, such as excitatory post-synaptic current, paired-pulse facilitation, and spike rate-dependent and spike number-dependent plasticity, were successfully implemented by utilizing the persistent photoconductivity effect of the IGZO channel stimulated by light. The synergy between the light stimulation and the EDL effect allowed the effective modulation of synaptic plasticity, enabling the control of memory levels, including the conversion of short-term memory to long-term memory. Furthermore, a Modified National Institute of Standards and Technology digit recognition simulation was performed using a three-layer artificial neural network model, achieving a high recognition rate of 90.5%. These results demonstrated a high application potential of the proposed optoelectronic synaptic transistors in neuromorphic visual systems.

Neuropeptide Y Signaling Regulates Recurrent Excitation in the Auditory Midbrain

Neuropeptides play key roles in shaping the organization and function of neuronal circuits. In the inferior colliculus (IC), which is in the auditory midbrain, Neuropeptide Y (NPY) is expressed by a class of GABAergic neurons that project locally and outside the IC. Most neurons in the IC have local axon collaterals; however, the organization and function of local circuits in the IC remain unknown. We previously found that excitatory neurons in the IC can express the NPY Y1 receptor (Y1R+) and application of the Y1R agonist, [Leu31, Pro34]-NPY (LP-NPY), decreases the excitability of Y1R+ neurons. As NPY signaling regulates recurrent excitation in other brain regions, we hypothesized that Y1R+ neurons form interconnected local circuits in the IC and that NPY decreases the strength of recurrent excitation in these circuits. To test this hypothesis, we used optogenetics to activate Y1R+ neurons in mice of both sexes while recording from other neurons in the ipsilateral IC. We found that nearly 80% of glutamatergic IC neurons express the Y1 receptor, providing extensive opportunities for NPY signaling to regulate local circuits. Additionally, Y1R+ neuron synapses exhibited modest short-term synaptic plasticity, suggesting that local excitatory circuits maintain their influence over computations during sustained stimuli. We further found that application of LP-NPY decreased recurrent excitation in the IC, suggesting that NPY signaling strongly regulates local circuit function in the auditory midbrain. Our findings show that Y1R+ excitatory neurons form interconnected local circuits in the IC, and their influence over local circuits is regulated by NPY signaling.SIGNIFICANCE STATEMENT Local networks play fundamental roles in shaping neuronal computations in the brain. The IC, localized in the auditory midbrain, plays an essential role in sound processing, but the organization of local circuits in the IC is largely unknown. Here, we show that IC neurons that express the Neuropeptide Y1 receptor (Y1R+ neurons) make up most of the excitatory neurons in the IC and form interconnected local circuits. Additionally, we found that NPY, which is a powerful neuromodulator known to shape neuronal activity in other brain regions, decreases the extensive recurrent excitation mediated by Y1R+ neurons in local IC circuits. Thus, our results suggest that local NPY signaling is a key regulator of auditory computations in the IC.

Short-term postsynaptic plasticity facilitates predictive tracking in continuous attractors

Introduction

The N-methyl-D-aspartate receptor (NMDAR) plays a critical role in synaptic transmission and is associated with various neurological and psychiatric disorders. Recently, a novel form of postsynaptic plasticity known as NMDAR-based short-term postsynaptic plasticity (STPP) has been identified. It has been suggested that long-lasting glutamate binding to NMDAR allows for the retention of input information in brain slices up to 500 ms, leading to response facilitation. However, the impact of STPP on the dynamics of neuronal populations remains unexplored.

Methods

In this study, we incorporated STPP into a continuous attractor neural network (CANN) model to investigate its effects on neural information encoding in populations of neurons. Unlike short-term facilitation, a form of presynaptic plasticity, the temporally enhanced synaptic efficacy resulting from STPP destabilizes the network state of the CANN by increasing its mobility.

Results

Our findings demonstrate that the inclusion of STPP in the CANN model enables the network state to predictively respond to a moving stimulus. This nontrivial dynamical effect facilitates the tracking of the anticipated stimulus, as the enhanced synaptic efficacy induced by STPP enhances the system's mobility.

Discussion

The discovered STPP-based mechanism for sensory prediction provides valuable insights into the potential development of brain-inspired computational algorithms for prediction. By elucidating the role of STPP in neural population dynamics, this study expands our understanding of the functional implications of NMDAR-related plasticity in information processing within the brain.

Conclusion

The incorporation of STPP into a CANN model highlights its influence on the mobility and predictive capabilities of neural networks. These findings contribute to our knowledge of STPP-based mechanisms and their potential applications in developing computational algorithms for sensory prediction.

Ferroelectric artificial synapse for neuromorphic computing and flexible applications

Research of artificial synapses is increasing in popularity with the development of bioelectronics and the appearance of wearable devices. Because the high-temperature treatment process of inorganic materials is not compatible with flexible substrates, organic ferroelectric materials that are easier to process have emerged as alternatives. An organic synaptic device based on P(VDF-TrFE) was prepared in this study. The device showed reliable P/E endurance over 104 cycles and a data storage retention capability at 80 °C over 104 s. Simultaneously, it possessed excellent synaptic functions, including short-term/ long-term synaptic plasticity and spike-timing-dependent plasticity. In addition, the ferroelectric performance of the device remained stable even under bending (7 mm bending radius) or after 500 bending cycles. This work shows that low-temperature processed organic ferroelectric materials can provide new ideas for the future development of wearable electronics and flexible artificial synapses.

Short-term plasticity in the spinal nociceptive system

ABSTRACT

Somatosensory information is delivered to neuronal networks of the dorsal horn (DH) of the spinal cord by the axons of primary afferent neurons that encode the intensity of peripheral sensory stimuli under the form of a code based on the frequency of action potential firing. The efficient processing of these messages within the DH involves frequency-tuned synapses, a phenomenon linked to their ability to display activity-dependent forms of short-term plasticity (STP). By affecting differently excitatory and inhibitory synaptic transmissions, these STP properties allow a powerful gain control in DH neuronal networks that may be critical for the integration of nociceptive messages before they are forwarded to the brain, where they may be ultimately interpreted as pain. Moreover, these STPs can be finely modulated by endogenous signaling molecules, such as neurosteroids, adenosine, or GABA. The STP properties of DH inhibitory synapses might also, at least in part, participate in the pain-relieving effect of nonpharmacological analgesic procedures, such as transcutaneous electrical nerve stimulation, electroacupuncture, or spinal cord stimulation. The properties of target-specific STP at inhibitory DH synapses and their possible contribution to electrical stimulation-induced reduction of hyperalgesic and allodynic states in chronic pain will be reviewed and discussed.

Activation of TRPV1 Channels Inhibits the Release of Acetylcholine and Improves Muscle Contractility in Mice

TRPV1 represents a non-selective transient receptor potential cation channel found not only in sensory neurons, but also in motor nerve endings and in skeletal muscle fibers. However, the role of TRPV1 in the functioning of the neuromuscular junction has not yet been fully established. In this study, the Levator Auris Longus muscle preparations were used to assess the effect of pharmacological activation of TRPV1 channels on neuromuscular transmission. The presence of TRPV1 channels in the nerve terminal and in the muscle fiber was confirmed by immunohistochemistry. It was verified by electrophysiology that the TRPV1 channel agonist capsaicin inhibits the acetylcholine release, and this effect was completely absent after preliminary application of the TRPV1 channel blocker SB 366791. Nerve stimulation revealed an increase of amplitude of isometric tetanic contractions upon application of capsaicin which was also eliminated after preliminary application of SB 366791. Similar data were obtained during direct muscle stimulation. Thus, pharmacological activation of TRPV1 channels affects the functioning of both the pre- and postsynaptic compartment of the neuromuscular junction. A moderate decrease in the amount of acetylcholine released from the motor nerve allows to maintain a reserve pool of the mediator to ensure a longer signal transmission process, and an increase in the force of muscle contraction, in its turn, also implies more effective physiological muscle activity in response to prolonged stimulation. This assumption is supported by the fact that when muscle was indirect stimulated with a fatigue protocol, muscle fatigue was attenuated in the presence of capsaicin.

Molecular definition of distinct active zone protein machineries for Ca2+ channel clustering and synaptic vesicle priming

Action potentials trigger neurotransmitter release with minimal delay. Active zones mediate this temporal precision by co-organizing primed vesicles with CaV2 Ca2+ channels. The presumed model is that scaffolding proteins directly tether primed vesicles to CaV2s. We find that CaV2 clustering and vesicle priming are executed by separate machineries. At hippocampal synapses, CaV2 nanoclusters are positioned at variable distances from those of the priming protein Munc13. The active zone organizer RIM anchors both proteins, but distinct interaction motifs independently execute these functions. In heterologous cells, Liprin-α and RIM from co-assemblies that are separate from CaV2-organizing complexes upon co-transfection. At synapses, Liprin-α1-4 knockout impairs vesicle priming, but not CaV2 clustering. The cell adhesion protein PTPσ recruits Liprin-α, RIM and Munc13 into priming complexes without co-clustering of CaV2s. We conclude that active zones consist of distinct complexes to organize CaV2s and vesicle priming, and Liprin-α and PTPσ specifically support priming site assembly.

The release of inhibition model reproduces kinetics and plasticity of neurotransmitter release in central synapses

Calcium-evoked release of neurotransmitters from synaptic vesicles (SVs) is catalysed by SNARE proteins. The predominant view is that, at rest, complete assembly of SNARE complexes is inhibited ('clamped') by synaptotagmin and complexin molecules. Calcium binding by synaptotagmins releases this fusion clamp and triggers fast SV exocytosis. However, this model has not been quantitatively tested over physiological timescales. Here we describe an experimentally constrained computational modelling framework to quantitatively assess how the molecular architecture of the fusion clamp affects SV exocytosis. Our results argue that the 'release-of-inhibition' model can indeed account for fast calcium-activated SV fusion, and that dual binding of synaptotagmin-1 and synaptotagmin-7 to the same SNARE complex enables synergistic regulation of the kinetics and plasticity of neurotransmitter release. The developed framework provides a powerful and adaptable tool to link the molecular biochemistry of presynaptic proteins to physiological data and efficiently test the plausibility of calcium-activated neurotransmitter release models.

In-Sensor Computing Realization Using Fully CMOS-Compatible TiN/HfOx-Based Neuristor Array

With the evolution of artificial intelligence, the explosive growth of data from sensory terminals gives rise to severe energy-efficiency bottleneck issues due to cumbersome data interactions among sensory, memory, and computing modules. Heterogeneous integration methods such as chiplet technology can significantly reduce unnecessary data movement; however, they fail to address the fundamental issue of the substantial time and energy overheads resulting from the physical separation of computing and sensory components. Brain-inspired in-sensor neuromorphic computing (ISNC) has plenty of room for such data-intensive applications. However, one key obstacle in developing ISNC systems is the lack of compatibility between material systems and manufacturing processes deployed in sensors and computing units. This study successfully addresses this challenge by implementing fully CMOS-compatible TiN/HfOx-based neuristor array. The developed ISNC system demonstrates several advantageous features, including multilevel analogue modulation, minimal dispersion, and no significant degradation in conductance (@125 °C). These characteristics enable stable and reproducible neuromorphic computing. Additionally, the device exhibits modulatable sensory and multi-store memory processes. Furthermore, the system achieves information recognition with a high accuracy rate of 93%, along with frequency selectivity and notable activity-dependent plasticity. This work provides a promising route to affordable and highly efficient sensory neuromorphic systems.

Dopamine-Regulated Plasticity in MoO3 Synaptic Transistors

Field-effect transistor-based biosensors have gained increasing interest due to their reactive surface to external stimuli and the adaptive feedback required for advanced sensing platforms in biohybrid neural interfaces. However, complex probing methods for surface functionalization remain a challenge that limits the industrial implementation of such devices. Herein, a simple, label-free biosensor based on molybdenum oxide (MoO3) with dopamine-regulated plasticity is demonstrated. Dopamine oxidation facilitated locally at the channel surface initiates a charge transfer mechanism between the molecule and the oxide, altering the channel conductance and successfully emulating the tunable synaptic weight by neurotransmitter activity. The oxygen level of the channel is shown to heavily affect the device's electrochemical properties, shifting from a nonreactive metallic characteristic to highly responsive semiconducting behavior. Controllable responsivity is achieved by optimizing the channel's dimension, which allows the devices to operate in wide ranges of dopamine concentration, from 100 nM to sub-mM levels, with excellent selectivity compared with K+, Na+, and Ca2+.

Superlow Power Consumption Memristor Based on Borphyrin-Deoxyribonucleic Acid Composite Films as Artificial Synapse for Neuromorphic Computing

Memristor synapses based on green and pollution-free organic materials are expected to facilitate biorealistic neuromorphic computing and to be an important step toward the next generation of green electronics. Metalloporphyrin is an organic compound that widely exists in nature with good biocompatibility and stable chemical properties, and has already been used to fabricate memristors. However, the application of metalloporphyrin-based memristors as synaptic devices still faces challenges, such as realizing a high switching ratio, low power consumption, and bidirectional conductance modulation. We developed a memristor that improves the resistive switching (RS) characteristics of Zn(II)meso-tetra(4-carboxyphenyl) porphine (ZnTCPP) by combining it with deoxyribonucleic acid (DNA) in a composite film. The as-fabricated ZnTCPP-DNA-based device showed excellent RS memory characteristics with a sufficiently high switching ratio of up to ∼104, super low power consumption of ∼39.56 nW, good cycling stability, and data retention capability. Moreover, bidirectional conductance modulation of the ZnTCPP-DNA-based device can be controlled by modulating the amplitudes, durations, and intervals of positive and negative pulses. The ZnTCPP-DNA-based device was used to successfully simulate a series of synaptic functions including long-term potentiation, long-term depression, spike time-dependent plasticity, paired-pulse facilitation, excitatory postsynaptic current, and human learning behavior, which demonstrates its potential applicability to neuromorphic devices. A two-layer artificial neural network was used to demonstrate the digit recognition ability of the ZnTCPP-DNA-based device, which reached 97.22% after 100 training iterations. These results create a new avenue for the research and development of green electronics and have major implications for green low-power neuromorphic computing in the future.

Impaired pre-synaptic plasticity and visual responses in auxilin-knockout mice

Auxilin (DNAJC6/PARK19), an endocytic co-chaperone, is essential for maintaining homeostasis in the readily releasable pool (RRP) by aiding clathrin-mediated uncoating of synaptic vesicles. Its loss-of-function mutations, observed in familial Parkinson's disease (PD), lead to basal ganglia motor deficits and cortical dysfunction. We discovered that auxilin-knockout (Aux-KO) mice exhibited impaired pre-synaptic plasticity in layer 4 to layer 2/3 pyramidal cell synapses in the primary visual cortex (V1), including reduced short-term facilitation and depression. Computational modeling revealed increased RRP refilling during short repetitive stimulation, which diminished during prolonged stimulation. Silicon probe recordings in V1 of Aux-KO mice demonstrated disrupted visual cortical circuit responses, including reduced orientation selectivity, compromised visual mismatch negativity, and shorter visual familiarity-evoked theta oscillations. Pupillometry analysis revealed an impaired optokinetic response. Auxilin-dependent pre-synaptic endocytosis dysfunction was associated with deficits in pre-synaptic plasticity, visual cortical functions, and eye movement prodromally or at the early stage of motor symptoms.

Input-specific synaptic depression shapes temporal integration in mouse visual cortex

Efficient sensory processing requires the nervous system to adjust to ongoing features of the environment. In primary visual cortex (V1), neuronal activity strongly depends on recent stimulus history. Existing models can explain effects of prolonged stimulus presentation but remain insufficient for explaining effects observed after shorter durations commonly encountered under natural conditions. We investigated the mechanisms driving adaptation in response to brief (100 ms) stimuli in L2/3 V1 neurons by performing in vivo whole-cell recordings to measure membrane potential and synaptic inputs. We find that rapid adaptation is generated by stimulus-specific suppression of excitatory and inhibitory synaptic inputs. Targeted optogenetic experiments reveal that these synaptic effects are due to input-specific short-term depression of transmission between layers 4 and 2/3. Thus, brief stimulus presentation engages a distinct adaptation mechanism from that previously reported in response to prolonged stimuli, enabling flexible control of sensory encoding across a wide range of timescales.

Porous crystalline materials for memories and neuromorphic computing systems

Porous crystalline materials usually include metal-organic frameworks (MOFs), covalent organic frameworks (COFs), hydrogen-bonded organic frameworks (HOFs) and zeolites, which exhibit exceptional porosity and structural/composition designability, promoting the increasing attention in memory and neuromorphic computing systems in the last decade. From both the perspective of materials and devices, it is crucial to provide a comprehensive and timely summary of the applications of porous crystalline materials in memory and neuromorphic computing systems to guide future research endeavors. Moreover, the utilization of porous crystalline materials in electronics necessitates a shift from powder synthesis to high-quality film preparation to ensure high device performance. This review highlights the strategies for preparing porous crystalline materials films and discusses their advancements in memory and neuromorphic electronics. It also provides a detailed comparative analysis and presents the existing challenges and future research directions, which can attract the experts from various fields (e.g., materials scientists, chemists, and engineers) with the aim of promoting the applications of porous crystalline materials in memory and neuromorphic computing systems.

A theory of hippocampal theta correlations accounting for extrinsic and intrinsic sequences

Hippocampal place cell sequences have been hypothesized to serve as diverse purposes as the induction of synaptic plasticity, formation and consolidation of long-term memories, or navigation and planning. During spatial behaviors of rodents, sequential firing of place cells at the theta timescale (known as theta sequences) encodes running trajectories, which can be considered as one-dimensional behavioral sequences of traversed locations. In a two-dimensional space, however, each single location can be visited along arbitrary one-dimensional running trajectories. Thus, a place cell will generally take part in multiple different theta sequences, raising questions about how this two-dimensional topology can be reconciled with the idea of hippocampal sequences underlying memory of (one-dimensional) episodes. Here, we propose a computational model of cornu ammonis 3 (CA3) and dentate gyrus (DG), where sensorimotor input drives the direction-dependent (extrinsic) theta sequences within CA3 reflecting the two-dimensional spatial topology, whereas the intrahippocampal CA3-DG projections concurrently produce intrinsic sequences that are independent of the specific running trajectory. Consistent with experimental data, intrinsic theta sequences are less prominent, but can nevertheless be detected during theta activity, thereby serving as running-direction independent landmark cues. We hypothesize that the intrinsic sequences largely reflect replay and preplay activity during non-theta states.

Adaptor protein AP-3 produces synaptic vesicles that release at high frequency by recruiting phospholipid flippase ATP8A1

Neural systems encode information in the frequency of action potentials, which is then decoded by synaptic transmission. However, the rapid, synchronous release of neurotransmitters depletes synaptic vesicles (SVs), limiting release at high firing rates. How then do synapses convey information about frequency? Here, we show in mouse hippocampal neurons and slices that the adaptor protein AP-3 makes a subset of SVs that respond specifically to high-frequency stimulation. Neurotransmitter transporters slot onto these SVs in different proportions, contributing to the distinct properties of release observed at different excitatory synapses. Proteomics reveals that AP-3 targets the phospholipid flippase ATP8A1 to SVs; loss of ATP8A1 recapitulates the defect in SV mobilization at high frequency observed with loss of AP-3. The mechanism involves recruitment of synapsin by the cytoplasmically oriented phosphatidylserine translocated by ATP8A1. Thus, ATP8A1 enables the subset of SVs made by AP-3 to release at high frequency.

Linking input- and cell-type-specific synaptic plasticity to the reinforcement of alcohol-seeking behavior

The reinforcement of voluntary alcohol-seeking behavior requires dopamine-dependent long-term synaptic plasticity in the striatum. Specifically, the long-term potentiation (LTP) of direct-pathway medium spiny neurons (dMSNs) in the dorsomedial striatum (DMS) promotes alcohol drinking. However, it remains unclear whether alcohol induces input-specific plasticity onto dMSNs and whether this plasticity directly drives instrumental conditioning. In this study, we found that voluntary alcohol intake selectively strengthened glutamatergic transmission from the medial prefrontal cortex (mPFC) to DMS dMSNs in mice. Importantly, mimicking this alcohol-induced potentiation by optogenetically self-stimulating mPFC→dMSN synapse with an LTP protocol was sufficient to drive the reinforcement of lever pressing in operant chambers. Conversely, induction of a post-pre spike timing-dependent LTD at this synapse time-locked to alcohol delivery during operant conditioning persistently decreased alcohol-seeking behavior. Our results establish a causal relationship between input- and cell-type-specific corticostriatal plasticity and the reinforcement of alcohol-seeking behavior. This provides a potential therapeutic strategy to restore normal cortical control of dysregulated basal ganglia circuitries in alcohol use disorder.