Short-term synaptic plasticity

Neural Functions Enabled by a Polarity-Switchable Nanofluidic Memristor

Reproducing neural functions with artificial nanofluidic systems has long been an aspirational goal for neuromorphic computing. In this study, neural functions, such as neural activation and synaptic plasticity, are successfully accomplished with a polarity-switchable nanofluidic memristor (PSNM), which is based on the anodized aluminum oxide (AAO) nanochannel array. The PSNM has unipolar memristive behavior at high electrolyte concentrations and bipolar memristive behavior at low electrolyte concentrations, which can emulate neural activation and synaptic plasticity, respectively. The mechanisms for the unipolar and bipolar memristive behaviors are related to the polyelectrolytic Wien (PEW) effect and ion accumulation/depletion effect, respectively. These findings are beneficial to the advancement of neuromorphic computing on nanofluidic platforms.

Neuromuscular Transmission in a Biological Context

Neuromuscular transmission is the process by which motor neurons activate muscle contraction and thus plays an essential role in generating the purposeful body movements that aid survival. While many features of this process are common throughout the Animal Kingdom, such as the release of transmitter in multimolecular "quanta," and the response to it by opening ligand-gated postsynaptic ion channels, there is also much diversity between and within species. Much of this diversity is associated with specialization for either slow, sustained movements such as maintain posture or fast but brief movements used during escape or prey capture. In invertebrates, with hydrostatic and exoskeletons, most motor neurons evoke graded depolarizations of the muscle which cause graded muscle contractions. By contrast, vertebrate motor neurons trigger action potentials in the muscle fibers which give rise to all-or-none contractions. The properties of neuromuscular transmission, in particular the intensity and persistence of transmitter release, reflect these differences. Neuromuscular transmission varies both between and within individual animals, which often have distinct tonic and phasic subsystems. Adaptive plasticity of neuromuscular transmission, on a range of time scales, occurs in many species. This article describes the main steps in neuromuscular transmission and how they vary in a number of "model" species, including C. elegans , Drosophila , zebrafish, mice, and humans. © 2024 American Physiological Society. Compr Physiol 14:5641-5702, 2024.

The synaptic vesicle cluster as a controller of pre- and postsynaptic structure and function

The synaptic vesicle cluster (SVC) is an essential component of chemical synapses, which provides neurotransmitter-loaded vesicles during synaptic activity, at the same time as also controlling the local concentrations of numerous exo- and endocytosis cofactors. In addition, the SVC hosts molecules that participate in other aspects of synaptic function, from cytoskeletal components to adhesion proteins, and affects the location and function of organelles such as mitochondria and the endoplasmic reticulum. We argue here that these features extend the functional involvement of the SVC in synapse formation, signalling and plasticity, as well as synapse stabilization and metabolism. We also propose that changes in the size of the SVC coalesce with changes in the postsynaptic compartment, supporting the interplay between pre- and postsynaptic dynamics. Thereby, the SVC could be seen as an 'all-in-one' regulator of synaptic structure and function, which should be investigated in more detail, to reveal molecular mechanisms that control synaptic function and heterogeneity.

The Brain's Best Kept Secret Is Its Degenerate Structure

Degeneracy is defined as multiple sets of solutions that can produce very similar system performance. Degeneracy is seen across phylogenetic scales, in all kinds of organisms. In neuroscience, degeneracy can be seen in the constellation of biophysical properties that produce a neuron's characteristic intrinsic properties and/or the constellation of mechanisms that determine circuit outputs or behavior. Here, we present examples of degeneracy at multiple levels of organization, from single-cell behavior, small circuits, large circuits, and, in cognition, drawing conclusions from work ranging from bacteria to human cognition. Degeneracy allows the individual-to-individual variability within a population that creates potential for evolution.

Metal-Organic Framework Nanofluidic Synapse

Chemical synapse completes the signaling through neurotransmitter-mediated ion flux, the emulation of which has been a long-standing obstacle in neuromorphic exploration. Here, we report metal-organic framework (MOF) nanofluidic synapses in which conjugated MOFs with abundant ionic storage sites underlie the ionic hysteresis and simultaneously serve as catalase mimetics that sensitively respond to neurotransmitter glutamate (Glu). Various neurosynaptic patterns with adaptable weights are realized via Glu-mediated chemical/ionic coupling. In particular, nonlinear Hebbian and anti-Hebbian learning in millisecond time ranges are achieved, akin to those of chemical synapses. Reversible biochemical in-memory encoding via enzymatic Glu clearance is also accomplished. Such results are prerequisites for highly bionic electrolytic computers.

Reconfigurable Resistive Switching Memory for Telegraph Code Sensing and Recognizing Reservoir Computing Systems

Reservoir computing (RC) system is based upon the reservoir layer, which non-linearly transforms input signals into high-dimensional states, facilitating simple training in the readout layer-a linear neural network. These layers require different types of devices-the former demonstrated as diffusive memristors and the latter prepared as drift memristors. The integration of these components can increase the structural complexity of RC system. Here, a reconfigurable resistive switching memory (RSM) capable of implementing both diffusive and drift dynamics is demonstrated. This reconfigurability is achieved by preparing a medium with a 3D ion transport channel (ITC), enabling precise control of the metal filament that determines memristor operation. The 3D ITC-RSM operates in a volatile threshold switching (TS) mode under a weak electric field and exhibits short-term dynamics that are confirmed to be applicable as reservoir elements in RC systems. Meanwhile, the 3D ITC-RSM operates in a non-volatile bipolar switching (BS) mode under a strong electric field, and the conductance modulation metrics forming the basis of synaptic weight update are validated, which can be utilized as readout elements in the readout layer. Finally, an RC system is designed for the application of reconfigurable 3D ITC-RSM, and performs real-time recognition on Morse code datasets.

Increasing the stability of electrolyte-gated organic synaptic transistors for neuromorphic implants

Electrolyte-gated organic synaptic transistors (EGOSTs) can have versatile synaptic plasticity in a single device, so they are promising as components of neuromorphic implants that are intended for use in neuroprosthetic electronic nerves that are energy-efficient and have simple system structure. With the advancement in transistor properties of EGOSTs, the commercialization of neuromorphic implants for practical long-term use requires consistent operation, so they must be stable in vivo. This requirement demands strategies that maintain electronic and ionic transport in the devices while implanted in the human body, and that are mechanically, environmentally, and operationally stable. Here, we cover the structure, working mechanisms, and electrical responses of EGOSTs. We then focus on strategies to ensure their stability to maintain these characteristics and prevent adverse effects on biological tissues. We also highlight state-of-the-art neuromorphic implants that incorporate these strategies. We conclude by presenting a perspective on improvements that are needed in EGOSTs to develop practical, neuromorphic implants that are long-term useable.

Rapid and local neuroestrogen synthesis supports long-term potentiation of hippocampal Schaffer collaterals-cornu ammonis 1 synapse in ovariectomized mice

In aging women, cognitive decline and increased risk of dementia have been associated with the cessation of ovarian hormones production at menopause. In the brain, presence of the key enzyme aromatase required for the synthesis of 17-β-estradiol (E2) allows for local production of E2 in absence of functional ovaries. Understanding how aromatase activity is regulated could help alleviate the cognitive symptoms. In female rodents, genetic or pharmacological reduction of aromatase activity over extended periods of time impair memory formation, decreases spine density, and hinders long-term potentiation (LTP) in the hippocampus. Conversely, increased excitatory neurotransmission resulting in rapid N-methyl-d-aspartic acid (NMDA) receptor activation rapidly promotes neuroestrogen synthesis. This rapid modulation of aromatase activity led us to address the hypothesis that acute neuroestrogens synthesis is necessary for LTP at the Schaffer collateral-cornu ammonis 1 (CA1) synapse in absence of circulating ovarian estrogens. To test this hypothesis, we did electrophysiological recordings of field excitatory postsynaptic potential (fEPSPs) in hippocampal slices obtained from ovariectomized mice. To assess the impact of neuroestrogens synthesis on LTP, we applied the specific aromatase inhibitor, letrozole, before the induction of LTP with a theta burst stimulation protocol. We found that blocking aromatase activity prevented LTP. Interestingly, exogenous E2 application, while blocking aromatase activity, was not sufficient to recover LTP in our model. Our results indicate the critical importance of rapid, activity-dependent local neuroestrogens synthesis, independent of circulating hormones for hippocampal synaptic plasticity in female rodents.

A Self-Driven Ga2O3 Memristor Synapse for Humanoid Robot Learning

In recent years, the rapid development of brain-inspired neuromorphic systems has created an imperative demand for artificial photonic synapses that operate with low power consumption. In this study, a self-driven memristor synapse based on gallium oxide (Ga2O3) nanowires is proposed and demonstrated successfully. This memristor synapse is capable of emulating a range of functionalities of biological synapses when exposed to 255 nm light stimulation. These functionalities encompass peak time-dependent plasticity, pulse facilitation, and memory learning capabilities. It exhibits an ultrahigh paired-pulse facilitation index of 158, indicating exceptional learning performance. The transition from short-term memory to long-term memory can be attributed to the remarkable relearning capabilities. Furthermore, the potential applications of the memristor synapse is showcased through the successful manipulation of a humanoid intelligent robot. Upon establishing artificial intelligence (AI) systems, the control commands originating from the synaptic device can drive the humanoid robot to perform various actions. Based on the memristor synapses, the autonomous feedback system of the humanoid robot facilitates a good collaboration between robotic actions and bio-inspired light perception. Therefore, this research opens up an effective way to advance the development of neuromorphic computing technologies, AI systems, and intelligent robots that demand ultra-low energy consumption.

Crosslinking-induced anion transport control for enhancing linearity in organic synaptic devices

Numerous studies on neuromorphic computing systems and their associated synaptic devices have been reported for the efficient processing of complex data. Among them, organic electrochemical transistors (OECTs) have attracted considerable attention owing to their advantages such as low cost, high scalability, and facile electrical modulation. However, the requirement of supplementary processing for ionic transport control to actualize or enhance synaptic attributes necessitates a compromise between their inherent benefits. Here, we developed a simple method, photoinduced crosslinking, which can control the structure of conjugated polymers in OECTs to improve ionic transport control. Crosslinked polymers increase the ion doping efficiency and allow sequential anion movements, which leads to high linearity in OECTs. The fabricated device also exhibited enhanced synaptic properties such as a long retention time, wide dynamic range, and high recognition accuracy. This innovative approach opens up new possibilities for the construction of next-generation artificial synapses.

Short term plasticity at hippocampal mossy fiber synapses

Short-term synaptic plasticity refers to the regulation of synapses by their past activity on time scales of milliseconds to minutes. Hippocampal mossy fiber synapses onto CA3 pyramidal cells (Mf-CA3 synapses) are endowed with remarkable forms of short-term synaptic plasticity expressed as facilitation of synaptic release by a factor of up to ten-fold. Three main forms of short-term plasticity are distinguished: 1) Frequency facilitation, which includes low frequency facilitation and train facilitation, operating in the range of tens of milliseconds to several seconds; 2) Post-tetanic potentiation triggered by trains of high frequency stimulation, which lasts several minutes; 3) Finally, depolarization-induced potentiation of excitation, based on retrograde signaling, with an onset and offset of several minutes. Here we describe the proposed mechanisms for short-term plasticity, mainly based on the kinetics of presynaptic Ca2+ transients and the Ca2+ sensor synaptotagmin 7, on cAMP-dependent mechanisms and readily releasable vesicle pool, and on the regulation of presynaptic K+ channels. We then review evidence for a physiological function of short-term plasticity of Mf-CA3 synapses in information transfer between the dentate gyrus and CA3 in conditions of natural spiking, and discuss how short-term plasticity counteracts robust feedforward inhibition in a frequency-dependent manner. Although DG-CA3 connections have long been proposed to play a role in memory, direct evidence for an implication of short-term plasticity at Mf-CA3 synapses is mostly lacking. The mechanistic knowledge gained on short-term plasticity at Mf-CA3 synapses should help in designing future experiments to directly test how this evolutionary conserved feature controls hippocampal circuit function in behavioural conditions.

A Flexible Laser-Induced Graphene Memristor with Volatile Switching for Neuromorphic Applications

Two-dimensional graphene and graphene-based materials are attracting increasing interest in neuromorphic computing applications by the implementation of memristive architectures that enable the closest solid-state equivalent to biological synapses and neurons. However, the state-of-the-art fabrication methodology involves routine use of high-temperature processes and multistepped chemical synthesis, often on a rigid substrate constraining the experimental exploration in the field to high-tech facilities. Here, we demonstrate the use of a one-step process using a commercial laser to fabricate laser-induced graphene (LIG) memristors directly on a flexible polyimide substrate. For the first time, a volatile resistive switching phenomenon is reported in the LIG without using any additional materials. The absence of any precursor or patterning mask greatly simplifies the process while reducing the cost and providing greater controllability. The fabricated memristors show multilevel resistance-switching characteristics with high endurance and tunable timing characteristics. The recovery time and the trigger pulse-dependent state change are shown to be highly suitable for its use as a synaptic element and in the realization of leaky-integrate and fire neuron in neuromorphic circuits.

Modulation of Neurotransmission by Acid-Sensing Ion Channels

ABSTRACT

Interstitial pH fluctuations occur normally in the brain and significantly modulate neuronal functions. Acid-sensing ion channels (ASICs), which serve as neuronal acid chemosensors, play important roles in synaptic plasticity, learning, and memory. However, the specific mechanisms by which ASICs influence neurotransmission remain elusive. Here, we report that ASICs modulate transmitter release and axonal excitability at a glutamatergic synapse in the rat and mouse hippocampus. Blocking ASIC1a channels with the tarantula peptide psalmotoxin 1 down-regulates basal transmission and alters short-term plasticity. Notably, the effect of psalmotoxin 1 on ASIC-mediated modulation is age-dependent, occurring only during a limited postnatal period (postnatal weeks 2-6). This finding suggests that protons, through the activation of ASICs, may act as modulators in synapse formation and maturation during early development.

Neuroplasticity elicited by peripheral immune challenge with a viral mimetic

Peripheral viral infections are well known to profoundly alter brain function; however detailed mechanisms of this immune-to-brain communication have not been deciphered. This review focuses on studies of cerebral effects of peripheral viral challenge employing intraperitoneal injection of a viral mimetic, polyinosinic-polycytidylic acid (PIC). In this paradigm, PIC challenge induces the acute phase response (APR) characterized by a transient surge of circulating inflammatory factors, primarily IFNβ, IL-6 and CXCL10. The blood-borne factors, in turn, elicit the generation of CXCL10 by hippocampal neurons. Neurons also express the cognate receptor of CXCL10, i.e., CXCR3 implicating the existence of autocrine/paracrine signaling. The CXCL10/CXCR3 axis mediates the ensuing neuroplastic changes manifested as neuronal hyperexcitability, seizure hypersusceptibility, and sickness behavior. Electrophysiological studies revealed that the neuroplastic changes entail the potentiation of excitatory synapses likely at both pre- and postsynaptic loci. Excitatory synaptic transmission is further augmented by PIC challenge-induced elevation of extracellular glutamate that is mediated by astrocytes. In addition, the hyperexcitability of neuronal circuits might involve the repression of inhibitory signaling. Accordingly, CXCL10 released by neurons activates microglia whose processes invade perisomatic inhibitory synapses, resulting in a partial detachment of the presynaptic terminals, and thus, de-inhibition. This process might be facilitated by the cerebral complement system, which is also upregulated and activated by PIC challenge. Moreover, CXCL10 stimulates the expression of neuronal c-fos protein, another index of hyperexcitability. The reviewed studies form a foundation for full elucidation of the fascinating intersection between peripheral viral infections and neuroplasticity. Because the activation of such pathways may constitute a serious comorbidity factor for neuropathological conditions, this research would advance the development of preventive strategies.

Characterization of subthalamic nucleus deep brain stimulation evoked resonant neural activity in a large animal model: A pilot study

Recent reports have described stimulation evoked resonant neural activity (ERNA) recorded in the subthalamic nucleus (STN) and globus pallidus internus (GPi) of patients during Deep Brain Stimulation (DBS) surgery. The constraints imposed during intraoperative recordings in patients limit the opportunity for in-depth study of new findings such as ERNA. In this pilot study, we leverage a large animal model to focus on detailed characterization of ERNA. Bilateral DBS leads were implanted in the STN in three ovine subjects and externalized for chronic use with custom stimulation and recording circuitry. ERNA was reliably recorded from the STN region in all three subjects with distinct specificity to recording and stimulation sites/contacts. Basic neural response characteristics such as input/output behavior, frequency response and strength/duration curves were evaluated. ERNA amplitude was highly dependent upon stimulation frequency, due to the interaction of the underlying resonant activity and the evoked response from each stimulus pulse. The results could be predicted by a mathematical model of constructive/destructive phase interference, and importantly, the evoked response latency. Significant time dependent dynamics in these evoked potentials were observed, which will be critically important to understand for future clinical applications. Based upon these recordings from leads in the STN region of healthy ovine subjects, these data confirm that DBS evokes high frequency resonant activity in the basal ganglia network. The clinical utility of ERNA remains to be demonstrated, but its direct association with DBS therapy makes it an interesting biomarker for potential use in contact selection and closed loop therapy.

Low-Cost, High-Efficiency Aluminum Zinc Oxide Synaptic Transistors: Blue LED Stimulation for Enhanced Neuromorphic Computing Applications

Neuromorphic devices are electronic devices that mimic the information processing methods of neurons and synapses, enabling them to perform multiple tasks simultaneously with low power consumption and exhibit learning ability. However, their large-scale production and efficient operation remain a challenge. Herein, we fabricated an aluminum-doped zinc oxide (AZO) synaptic transistor via solution-based spin-coating. The transistor is characterized by low production costs and high performance. It demonstrates high responsiveness under UV laser illumination. In addition, it exhibits effective synaptic behaviors under blue LED illumination, indicating high-efficiency operation. The paired-pulse facilitation (PPF) index measured from optical stimulus modulation was 179.6%, indicating strong synaptic connectivity and effective neural communication and processing. Furthermore, by modulating the blue LED light pulse frequency, an excitatory postsynaptic current gain of 4.3 was achieved, demonstrating efficient neuromorphic functionality. This study shows that AZO synaptic transistors are promising candidates for artificial synaptic devices.

Synaptic Transistors Using Scalable Graphene Nanoribbons

Graphene has demonstrated potential for use in neuromorphic electronics due to its superior electrical properties. However, these devices are all based on graphene sheets without patterning, restricting its applications. Here, we demonstrate a graphene nanoribbon synaptic transistor (GNST), with the graphene nanoribbon (GNR) channels fabricated using an electro-hydrodynamically printed nanowire array as lithographic masks for scalable fabrication. The GNST shows tunable synaptic plasticity by spike duration, frequency, and number. Moreover, the device is energy-efficient and ambipolar and shows a regulated response by nanoribbon width. The characteristics of GNSTs are applicable to pattern recognition, showing an accuracy of 84.5%. The device is applicable to Pavlov's classical conditioning. This study reports the first synaptic transistor based on GNRs, providing new insights into future neuromorphic electronics.

Optoelectronic synapses with chemical-electric behaviors in gallium nitride semiconductors for biorealistic neuromorphic functionality

Optoelectronic synapses, leveraging the integration of classic photo-electric effect with synaptic plasticity, are emerging as building blocks for artificial vision and photonic neuromorphic computing. However, the fundamental working principles of most optoelectronic synapses mainly rely on physical behaviors while missing chemical-electric synaptic processes critical for mimicking biorealistic neuromorphic functionality. Herein, we report a photoelectrochemical synaptic device based on p-AlGaN/n-GaN semiconductor nanowires to incorporate chemical-electric synaptic behaviors into optoelectronic synapses, demonstrating unparalleled dual-modal plasticity and chemically-regulated neuromorphic functions through the interplay of internal photo-electric and external electrolyte-mediated chemical-electric processes. Electrical modulation by implementing closed or open-circuit enables switching of optoelectronic synaptic operation between short-term and long-term plasticity. Furthermore, inspired by transmembrane receptors that connect extracellular and intracellular events, synaptic responses can also be effectively amplified by applying chemical modifications to nanowire surfaces, which tune external and internal charge behaviors. Notably, under varied external electrolyte environments (ion/molecule species and concentrations), our device successfully mimics chemically-regulated synaptic activities and emulates intricate oxidative stress-induced biological phenomena. Essentially, we demonstrate that through the nanowire photoelectrochemical synapse configuration, optoelectronic synapses can be incorporated with chemical-electric behaviors to bridge the gap between classic optoelectronic synapses and biological synapses, providing a promising platform for multifunctional neuromorphic applications.

A Photoelectrochemical Retinomorphic Synapse

Reproducing human visual functions with artificial devices is a long-standing goal of the neuromorphic domain. However, emulating the chemical language communication of the visual system in fluids remains a grand challenge. Here, a "multi-color" hydrogel-based photoelectrochemical retinomorphic synapse is reported with unique chemical-ionic-electrical signaling in an aqueous electrolyte that enables, e.g., color perception and biomolecule-mediated synaptic plasticity. Based on the specific enzyme-catalyzed chromogenic reactions, three multifunctional colored hydrogels are developed, which can not only synergize with the Bi2S3 photogate to recognize the primary colors but also synergize with a given polymeric channel to promote the long-term memory of the system. A synaptic array is further constructed for sensing color images and biomolecule-coded information communication. Taking advantage of the versatile biochemistry, the biochemical-driven reversible photoelectric response of the cone cell is further mimicked. This work introduces rich chemical designs into retinomorphic devices, providing a perspective for replicating the human visual system in fluids.

LGI1 Autoantibodies Enhance Synaptic Transmission by Presynaptic Kv1 Loss and Increased Action Potential Broadening

BACKGROUND AND OBJECTIVES

Autoantibodies against the protein leucine-rich glioma inactivated 1 (LGI1) cause the most common subtype of autoimmune encephalitis with predominant involvement of the limbic system, associated with seizures and memory deficits. LGI1 and its receptor ADAM22 are part of a transsynaptic protein complex that includes several proteins involved in presynaptic neurotransmitter release and postsynaptic glutamate sensing. Autoantibodies against LGI1 increase excitatory synaptic strength, but studies that genetically disrupt the LGI1-ADAM22 complex report a reduction in postsynaptic glutamate receptor-mediated responses. Thus, the mechanisms underlying the increased synaptic strength induced by LGI1 autoantibodies remain elusive, and the contributions of presynaptic molecules to the LGI1-transsynaptic complex remain unclear. We therefore investigated the presynaptic mechanisms that mediate autoantibody-induced synaptic strengthening.

METHODS

We studied the effects of patient-derived purified polyclonal LGI1 autoantibodies on synaptic structure and function by combining direct patch-clamp recordings from presynaptic boutons and somata of hippocampal neurons with super-resolution light and electron microscopy of hippocampal cultures and brain slices. We also identified the protein domain mediating the presynaptic effect using domain-specific patient-derived monoclonal antibodies.

RESULTS

LGI1 autoantibodies dose-dependently increased short-term depression during high-frequency transmission, consistent with increased release probability. The increased neurotransmission was not related to presynaptic calcium channels because presynaptic Cav2.1 channel density, calcium current amplitude, and calcium channel gating were unaffected by LGI1 autoantibodies. By contrast, application of LGI1 autoantibodies homogeneously reduced Kv1.1 and Kv1.2 channel density on the surface of presynaptic boutons. Direct presynaptic patch-clamp recordings revealed that LGI1 autoantibodies cause a pronounced broadening of the presynaptic action potential. Domain-specific effects of LGI1 autoantibodies were analyzed at the neuronal soma. Somatic action potential broadening was induced by polyclonal LGI1 autoantibodies and patient-derived monoclonal autoantibodies targeting the epitempin domain, but not the leucin-rich repeat domain.

DISCUSSION

Our results indicate that LGI1 autoantibodies reduce the density of both Kv1.1 and Kv1.2 on presynaptic boutons, without actions on calcium channel density or function, thereby broadening the presynaptic action potential and increasing neurotransmitter release. This study provides a molecular explanation for the neuronal hyperactivity observed in patients with LGI1 autoantibodies.

Neuromorphic Nanoionics for Human-Machine Interaction: From Materials to Applications

Human-machine interaction (HMI) technology has undergone significant advancements in recent years, enabling seamless communication between humans and machines. Its expansion has extended into various emerging domains, including human healthcare, machine perception, and biointerfaces, thereby magnifying the demand for advanced intelligent technologies. Neuromorphic computing, a paradigm rooted in nanoionic devices that emulate the operations and architecture of the human brain, has emerged as a powerful tool for highly efficient information processing. This paper delivers a comprehensive review of recent developments in nanoionic device-based neuromorphic computing technologies and their pivotal role in shaping the next-generation of HMI. Through a detailed examination of fundamental mechanisms and behaviors, the paper explores the ability of nanoionic memristors and ion-gated transistors to emulate the intricate functions of neurons and synapses. Crucial performance metrics, such as reliability, energy efficiency, flexibility, and biocompatibility, are rigorously evaluated. Potential applications, challenges, and opportunities of using the neuromorphic computing technologies in emerging HMI technologies, are discussed and outlooked, shedding light on the fusion of humans with machines.

Retinoic Acid-Dependent Loss of Synaptic Output from Bipolar Cells Impairs Visual Information Processing in Inherited Retinal Degeneration

In retinitis pigmentosa (RP), rod and cone photoreceptors degenerate, depriving downstream neurons of light-sensitive input, leading to vision impairment or blindness. Although downstream neurons survive, some undergo morphological and physiological remodeling. Bipolar cells (BCs) link photoreceptors, which sense light, to retinal ganglion cells (RGCs), which send information to the brain. While photoreceptor loss disrupts input synapses to BCs, whether BC output synapses remodel has remained unknown. Here we report that synaptic output from BCs plummets in RP mouse models of both sexes owing to loss of voltage-gated Ca2+ channels. Remodeling reduces the reliability of synaptic output to repeated optogenetic stimuli, causing RGC firing to fail at high-stimulus frequencies. Fortunately, functional remodeling of BCs can be reversed by inhibiting the retinoic acid receptor (RAR). RAR inhibitors targeted to BCs present a new therapeutic opportunity for mitigating detrimental effects of remodeling on signals initiated either by surviving photoreceptors or by vision-restoring tools.

Synaptotagmins 3 and 7 mediate the majority of asynchronous release from synapses in the cerebellum and hippocampus

Neurotransmitter release consists of rapid synchronous release followed by longer-lasting asynchronous release (AR). Although the presynaptic proteins that trigger synchronous release are well understood, the mechanisms for AR remain unclear. AR is sustained by low concentrations of intracellular Ca2+ and Sr2+, suggesting the involvement of sensors with high affinities for both ions. Synaptotagmin 7 (SYT7) partly mediates AR, but substantial AR persists in the absence of SYT7. The closely related SYT3 binds Ca2+ and Sr2+ with high affinity, making it a promising candidate to mediate AR. Here, we use knockout mice to study the contribution of SYT3 and SYT7 to AR at cerebellar and hippocampal synapses. AR is dramatically reduced when both isoforms are absent, which alters the number and timing of postsynaptic action potentials. Our results confirm the long-standing prediction that SYT3 mediates AR and show that SYT3 and SYT7 act as dominant mechanisms for AR at three central synapses.

Physical Reservoir Computing Using van der Waals Ferroelectrics for Acoustic Keyword Spotting

Acoustic keyword spotting (KWS) plays a pivotal role in the voice-activated systems of artificial intelligence (AI), allowing for hands-free interactions between humans and smart devices through information retrieval of the voice commands. The cloud computing technology integrated with the artificial neural networks has been employed to execute the KWS tasks, which however suffers from propagation delay and the risk of privacy breach. Here, we report a single-node reservoir computing (RC) system based on the CuInP2S6 (CIPS)/graphene heterostructure planar device for implementing the KWS task with low computation cost. Through deliberately tuning the Schottky barrier height at the ferroelectric CIPS interfaces for the thermionic injection and transport of the electrons, the typical nonlinear current response and fading memory characteristics are achieved in the device. Additionally, the device exhibits diverse synaptic plasticity with an excellent separation capability of the temporal information. We construct a RC system through employing the ferroelectric device as the physical node to spot the acoustic keywords, i.e., the natural numbers from 1 to 9 based on simulation, in which the system demonstrates outstanding performance with high accuracy rate (>94.6%) and recall rate (>92.0%). Our work promises physical RC in single-node configuration as a prospective computing platform to process the acoustic keywords, promoting its applications in the artificial auditory system at the edge.

Presynaptic quantal size enhancement counteracts post-tetanic release depression

Repetitive synaptic stimulation can induce different forms of synaptic plasticity but may also limit the robustness of synaptic transmission by exhausting key resources. Little is known about how synaptic transmission is stabilized after high-frequency stimulation. In the present study, we observed that tetanic stimulation of the Drosophila neuromuscular junction (NMJ) decreases quantal content, release-ready vesicle pool size and synaptic vesicle density for minutes after stimulation. This was accompanied by a pronounced increase in quantal size. Interestingly, action potential-evoked synaptic transmission remained largely unchanged. EPSC amplitude fluctuation analysis confirmed the post-tetanic increase in quantal size and the decrease in quantal content, suggesting that the quantal size increase counteracts release depression to maintain evoked transmission. The magnitude of the post-tetanic quantal size increase and release depression correlated with stimulation frequency and duration, indicating activity-dependent stabilization of synaptic transmission. The post-tetanic quantal size increase persisted after genetic ablation of the glutamate receptor subunits GluRIIA or GluRIIB, and glutamate receptor calcium permeability, as well as blockade of postsynaptic calcium channels. By contrast, it was strongly attenuated by pharmacological or presynaptic genetic perturbation of the GTPase dynamin. Similar observations were made after inhibition of the H+-ATPase, suggesting that the quantal size increase is presynaptically driven. Additionally, dynamin and H+-ATPase perturbation resulted in a post-tetanic decrease in evoked amplitudes. Finally, we observed an increase in synaptic vesicle diameter after tetanic stimulation. Thus, a presynaptically-driven quantal size increase, likely mediated by larger synaptic vesicles, counterbalances post-tetanic release depression, thereby conferring robustness to synaptic transmission on the minute time scale. KEY POINTS: Many synapses transmit robustly after sustained activity despite the limitation of key resources, such as release-ready synaptic vesicles. We report robust synaptic transmission after sustained high-frequency stimulation of the Drosophila neuromuscular junction despite a reduction in release-ready vesicle number. An increased postsynaptic response to individual vesicles, likely driven by an increase in vesicle size due to endocytosis defects, stabilizes synaptic efficacy for minutes after sustained activity. Our study provides novel insights into the mechanisms governing synaptic stability after sustained neural activity.

Neuromorphic learning and recognition in WO3-xthin film-based forming-free flexible electronic synapses

In pursuing advanced neuromorphic applications, this study introduces the successful engineering of a flexible electronic synapse based on WO3-x, structured as W/WO3-x/Pt/Muscovite-Mica. This artificial synapse is designed to emulate crucial learning behaviors fundamental to in-memory computing. We systematically explore synaptic plasticity dynamics by implementing pulse measurements capturing potentiation and depression traits akin to biological synapses under flat and different bending conditions, thereby highlighting its potential suitability for flexible electronic applications. The findings demonstrate that the memristor accurately replicates essential properties of biological synapses, including short-term plasticity (STP), long-term plasticity (LTP), and the intriguing transition from STP to LTP. Furthermore, other variables are investigated, such as paired-pulse facilitation, spike rate-dependent plasticity, spike time-dependent plasticity, pulse duration-dependent plasticity, and pulse amplitude-dependent plasticity. Utilizing data from flat and differently bent synapses, neural network simulations for pattern recognition tasks using the Modified National Institute of Standards and Technology dataset reveal a high recognition accuracy of ∼95% with a fast learning speed that requires only 15 epochs to reach saturation.

Volatile and Nonvolatile Programmable Iontronic Memristor with Lithium Imbued TiOx for Neuromorphic Computing Applications

We demonstrate a lithium (Li) imbued TiOx iontronic device that exhibits synapse-like short-term plasticity behavior without requiring a forming process beforehand or a compliance current during switching. A solid-state electrolyte lithium phosphorus oxynitride (LiPON) behaves as the ion source, and the embedding and releasing of Li ions inside the cathodic like TiOx renders volatile conductance responses from the device and offers a natural platform for hardware simulating neuron functionalities. Besides, these devices possess high uniformity and great endurance as no conductive filaments are present. Different short-term pulse-based phenomena, including paired pulse facilitation, post-tetanic potentiation, and spike rate-dependent plasticity, were observed with self-relaxation characteristics. Based on the voltage excitation period, the time scale of the volatile memory can be tuned. Temperature measurement reveals the ion displacement-induced conductance channels become frozen below 220 K. In addition, the volatile analog devices can be configured into nonvolatile memory units with multibit storage capabilities after an electroforming process. Therefore, on the same platform, we can configure volatile units as nonlinear dynamic reservoirs for performing neuromorphic training and the nonvolatile units as the weight storage layer. We proceed to use voice recognition as an example with the tunable time constant relationship and obtain 94.4% accuracy with a minimal training data set. Thus, this iontronic platform can effectively process and update temporal information for reservoir and neuromorphic computing paradigms.

Sleep maintains excitatory synapse diversity in the cortex and hippocampus

Insufficient sleep is a global problem with serious consequences for cognition and mental health.1 Synapses play a central role in many aspects of cognition, including the crucial function of memory consolidation during sleep.2 Interference with the normal expression or function of synapse proteins is a cause of cognitive, mood, and other behavioral problems in over 130 brain disorders.3 Sleep deprivation (SD) has also been reported to alter synapse protein composition and synapse number, although with conflicting results.4,5,6,7 In our study, we conducted synaptome mapping of excitatory synapses in 125 regions of the mouse brain and found that sleep deprivation selectively reduces synapse diversity in the cortex and in the CA1 region of the hippocampus. Sleep deprivation targeted specific types and subtypes of excitatory synapses while maintaining total synapse density (synapse number/area). Synapse subtypes with longer protein lifetimes exhibited resilience to sleep deprivation, similar to observations in aging and genetic perturbations. Moreover, the altered synaptome architecture affected the responses to neural oscillations, suggesting that sleep plays a vital role in preserving cognitive function by maintaining the brain's synaptome architecture.

Social play behavior is driven by glycine-dependent mechanisms

Social play is pervasive in juvenile mammals, yet it is poorly understood in terms of its underlying brain mechanisms. Specifically, we do not know why young animals are most playful and why most adults cease to social play. Here, we analyze the synaptic mechanisms underlying social play. We found that blocking the rat periaqueductal gray (PAG) interfered with social play. Furthermore, an age-related decrease of neural firing in the PAG is associated with a decrease in synaptic release of glycine. Most importantly, modulation of glycine concentration-apparently acting on the glycinergic binding site of the N-methyl-D-aspartate (NMDA) receptor-not only strongly modulates social play but can also reverse the age-related decline in social play. In conclusion, we demonstrate that social play critically depends on the neurotransmitter glycine within the PAG.

Artificial organic afferent nerves enable closed-loop tactile feedback for intelligent robot

The emulation of tactile sensory nerves to achieve advanced sensory functions in robotics with artificial intelligence is of great interest. However, such devices remain bulky and lack reliable competence to functionalize further synaptic devices with proprioceptive feedback. Here, we report an artificial organic afferent nerve with low operating bias (-0.6 V) achieved by integrating a pressure-activated organic electrochemical synaptic transistor and artificial mechanoreceptors. The dendritic integration function for neurorobotics is achieved to perceive directional movement of object, further reducing the control complexity by exploiting the distributed and parallel networks. An intelligent robot assembled with artificial afferent nerve, coupled with a closed-loop feedback program is demonstrated to rapidly implement slip recognition and prevention actions upon occurrence of object slippage. The spatiotemporal features of tactile patterns are well differentiated with a high recognition accuracy after processing spike-encoded signals with deep learning model. This work represents a breakthrough in mimicking synaptic behaviors, which is essential for next-generation intelligent neurorobotics and low-power biomimetic electronics.

Dose-response relationship between computerized cognitive training and cognitive improvement

Although computerized cognitive training (CCT) is an effective digital intervention for cognitive impairment, its dose-response relationship is understudied. This retrospective cohort study explores the association between training dose and cognitive improvement to find the optimal CCT dose. From 2017 to 2022, 8,709 participants with subjective cognitive decline, mild cognitive impairment, and mild dementia were analyzed. CCT exposure varied in daily dose and frequency, with cognitive improvement measured weekly using Cognitive Index. A mixed-effects model revealed significant Cognitive Index increases across most dose groups before reaching the optimal dose. For participants under 60 years, the optimal dose was 25 to <30 min per day for 6 days a week. For those 60 years or older, it was 50 to <55 min per day for 6 days a week. These findings highlight a dose-dependent effect in CCT, suggesting age-specific optimal dosing for cognitive improvement.

Single neuromorphic memristor closely emulates multiple synaptic mechanisms for energy efficient neural networks

Biological neural networks do not only include long-term memory and weight multiplication capabilities, as commonly assumed in artificial neural networks, but also more complex functions such as short-term memory, short-term plasticity, and meta-plasticity - all collocated within each synapse. Here, we demonstrate memristive nano-devices based on SrTiO3 that inherently emulate all these synaptic functions. These memristors operate in a non-filamentary, low conductance regime, which enables stable and energy efficient operation. They can act as multi-functional hardware synapses in a class of bio-inspired deep neural networks (DNN) that make use of both long- and short-term synaptic dynamics and are capable of meta-learning or learning-to-learn. The resulting bio-inspired DNN is then trained to play the video game Atari Pong, a complex reinforcement learning task in a dynamic environment. Our analysis shows that the energy consumption of the DNN with multi-functional memristive synapses decreases by about two orders of magnitude as compared to a pure GPU implementation. Based on this finding, we infer that memristive devices with a better emulation of the synaptic functionalities do not only broaden the applicability of neuromorphic computing, but could also improve the performance and energy costs of certain artificial intelligence applications.

A high-performance organic lithium salt-doped OFET with the optical radical effect for photoelectric pulse synaptic simulation and neuromorphic memory learning

Simulation of synaptic characteristics is essential for the application of organic field effect transistors (OFETs) in neural morphology. Although excellent performance, including bias stability and mobility, as well as photoelectric pulse synaptic simulation, has been achieved in SiO2-gated OFETs with PDVT-10 as an organic channel, there are relatively few studies on photoelectric pulse synaptic simulation of electrolyte-gated OFETs based on environmentally friendly and low-voltage operation. Herein, synaptic transistors based on organic semiconductors are reported to simulate the photoelectric pulse response by developing solution-based organic semiconductor PDVT-10, and polyvinyl alcohol (PVA) with an electric double layer (EDL) effect to act as a channel and gate dielectric layer, respectively, and organic lithium salt-doped PVA is used to enhance the EDL effect. The presence of electrical pulses in doped devices not only achieves basic electrical synaptic characteristics, but also significantly realizes the long-term characteristics, pain perception, memory and sensitization applications. Furthermore, the introduction of photoinitiator molecules into the channel layer leads to improved photosynaptic performances by using light-induced free radicals, and the photoelectric synergistic effect has been actualized by introducing heterojunction architecture. This work provides promising prospects for achieving photoelectric pulse modulation based on organic synaptic devices, which shows great potential for the development of artificial intelligence.

Adaptation in the visual system: Networked fatigue or suppressed prediction error signalling?

Our brains are constantly adapting to changes in our visual environments. Neural adaptation exerts a persistent influence on the activity of sensory neurons and our perceptual experience, however there is a lack of consensus regarding how adaptation is implemented in the visual system. One account describes fatigue-based mechanisms embedded within local networks of stimulus-selective neurons (networked fatigue models). Another depicts adaptation as a product of stimulus expectations (predictive coding models). In this review, I evaluate neuroimaging and psychophysical evidence that poses fundamental problems for predictive coding models of neural adaptation. Specifically, I discuss observations of distinct repetition and expectation effects, as well as incorrect predictions of repulsive adaptation aftereffects made by predictive coding accounts. Based on this evidence, I argue that networked fatigue models provide a more parsimonious account of adaptation effects in the visual system. Although stimulus expectations can be formed based on recent stimulation history, any consequences of these expectations are likely to co-occur (or interact) with effects of fatigue-based adaptation. I conclude by proposing novel, testable hypotheses relating to interactions between fatigue-based adaptation and other predictive processes, focusing on stimulus feature extrapolation phenomena.

Mitochondrial plasticity and synaptic plasticity crosstalk; in health and Alzheimer's disease

Synaptic plasticity is believed to underlie the cellular and molecular basis of memory formation. Mitochondria are one of the main organelles involved in metabolism and energy maintenance as plastic organelles that change morphologically and functionally in response to cellular needs and regulate synaptic function and plasticity through multiple mechanisms, including ATP generation, calcium homeostasis, and biogenesis. An increased neuronal activity enhances synaptic efficiency, during which mitochondria's spatial distribution and morphology change significantly. These organelles build up in the pre-and postsynaptic zones to produce ATP, which is necessary for several synaptic processes like neurotransmitter release and recycling. Mitochondria also regulate calcium homeostasis by buffering intracellular calcium, which ensures proper synaptic activity. Furthermore, mitochondria in the presynaptic terminal have distinct morphological properties compared to dendritic or postsynaptic mitochondria. This specialization enables precise control of synaptic activity and plasticity. Mitochondrial dysfunction has been linked to synaptic failure in many neurodegenerative disorders, like Alzheimer's disease (AD). In AD, malfunctioning mitochondria cause delays in synaptic vesicle release and recycling, ionic gradient imbalances, and mostly synaptic failure. This review emphasizes mitochondrial plasticity's contribution to synaptic function. It also explores the profound effect of mitochondrial malfunction on neurodegenerative disorders, focusing on AD, and provides an overview of how they sustain cellular health under normal conditions and how their malfunction contributes to neurodegenerative diseases, highlighting their potential as a therapeutic target for such conditions.

Dynamics of spike transmission and suppression between principal cells and interneurons in the hippocampus and entorhinal cortex

Synaptic excitation and inhibition are essential for neuronal communication. However, the variables that regulate synaptic excitation and inhibition in the intact brain remain largely unknown. Here, we examined how spike transmission and suppression between principal cells (PCs) and interneurons (INTs) are modulated by activity history, brain state, cell type, and somatic distance between presynaptic and postsynaptic neurons by applying cross-correlogram analyses to datasets recorded from the dorsal hippocampus and medial entorhinal cortex (MEC) of 11 male behaving and sleeping Long Evans rats. The strength, temporal delay, and brain-state dependency of the spike transmission and suppression depended on the subregions/layers. The spike transmission probability of PC-INT excitatory pairs that showed short-term depression versus short-term facilitation was higher in CA1 and lower in CA3. Likewise, the intersomatic distance affected the proportion of PC-INT excitatory pairs that showed short-term depression and facilitation in the opposite manner in CA1 compared with CA3. The time constant of depression was longer, while that of facilitation was shorter in MEC than in CA1 and CA3. During sharp-wave ripples, spike transmission showed a larger gain in the MEC than in CA1 and CA3. The intersomatic distance affected the spike transmission gain during sharp-wave ripples differently in CA1 versus CA3. A subgroup of MEC layer 3 (EC3) INTs preferentially received excitatory inputs from and inhibited MEC layer 2 (EC2) PCs. The EC2 PC-EC3 INT excitatory pairs, most of which showed short-term depression, exhibited higher spike transmission probabilities than the EC2 PC-EC2 INT and EC3 PC-EC3 INT excitatory pairs. EC2 putative stellate cells exhibited stronger spike transmission to and received weaker spike suppression from EC3 INTs than EC2 putative pyramidal cells. This study provides detailed comparisons of monosynaptic interaction dynamics in the hippocampal-entorhinal loop, which may help to elucidate circuit operations.

Modulation of multisensory nociceptive neurons in monkey cortical area 7b and behavioral correlates

Wide-range thermoreceptive neurons (WRT-EN) in monkey cortical area 7b that encoded innocuous and nocuous cutaneous thermal and threatening visuosensory stimulation with high fidelity were studied to identify their multisensory integrative response properties. Emphasis was given to characterizing the spatial and temporal effects of threatening visuosensory input on the thermal stimulus-response properties of these multisensory nociceptive neurons. Threatening visuosensory stimulation was most efficacious in modulating thermal evoked responses when presented as a downward ("looming"), spatially congruent, approaching and closely proximal target in relation to the somatosensory receptive field. Both temporal alignment and misalignment of spatially aligned threatening visual and thermal stimulation significantly increased mean discharge frequencies above those evoked by thermal stimulation alone, particularly at near noxious (43°C) and mildly noxious (45°C) temperatures. The enhanced multisensory discharge frequencies were equivalent to the discharge frequency evoked by overtly noxious thermal stimulation alone at 47°C (monkey pain tolerance threshold). A significant increase in behavioral mean escape frequency with shorter escape latency was evoked by multisensory stimulation at near noxious temperature (43°C), which was equivalent to that evoked by noxious stimulation alone (47°C). The remarkable concordance of elevating both neural discharge and escape frequency from a nonnociceptive and prepain level by near noxious thermal stimulation to a nociceptive and pain level by multisensory visual and near noxious thermal stimulation and integration is an elegantly designed defensive neural mechanism that in effect lowers both nociceptive response and pain thresholds to preemptively engage nocifensive behavior and, consequently, avert impending and actual injurious noxious thermal stimulation.NEW & NOTEWORTHY Multisensory nociceptive neurons in cortical area 7b are engaged in integration of threatening visuosensory and a wide range of innocuous and nocuous somatosensory (thermoreceptive) inputs. The enhancement of neuronal activity and escape behavior in monkey by multisensory integration is consistent and supportive of human psychophysical studies. The spatial features of visuosensory stimulation in peripersonal space in relation to somatic stimulation in personal space are critical to multisensory integration, nociception, nocifensive behavior, and pain.

Attentional selection and communication through coherence: Scope and limitations

Synchronous neural oscillations are strongly associated with a variety of perceptual, cognitive, and behavioural processes. It has been proposed that the role of the synchronous oscillations in these processes is to facilitate information transmission between brain areas, the 'communication through coherence,' or CTC hypothesis. The details of how this mechanism would work, however, and its causal status, are still unclear. Here we investigate computationally a proposed mechanism for selective attention that directly implicates the CTC as causal. The mechanism involves alpha band (about 10 Hz) oscillations, originating in the pulvinar nucleus of the thalamus, being sent to communicating cortical areas, organizing gamma (about 40 Hz) oscillations there, and thus facilitating phase coherence and communication between them. This is proposed to happen contingent on control signals sent from higher-level cortical areas to the thalamic reticular nucleus, which controls the alpha oscillations sent to cortex by the pulvinar. We studied the scope of this mechanism in parameter space, and limitations implied by this scope, using a computational implementation of our conceptual model. Our results indicate that, although the CTC-based mechanism can account for some effects of top-down and bottom-up attentional selection, its limitations indicate that an alternative mechanism, in which oscillatory coherence is caused by communication between brain areas rather than being a causal factor for it, might operate in addition to, or even instead of, the CTC mechanism.

Dopamine biases decisions by limiting temporal integration

Motivations bias our responses to stimuli, producing behavioural outcomes that match our needs and goals. Here we describe a mechanism behind this phenomenon: adjusting the time over which stimulus-derived information is permitted to accumulate towards a decision. As a Drosophila copulation progresses, the male becomes less likely to continue mating through challenges1-3. We show that a set of copulation decision neurons (CDNs) flexibly integrates information about competing drives to mediate this decision. Early in mating, dopamine signalling restricts CDN integration time by potentiating Ca2+/calmodulin-dependent protein kinase II (CaMKII) activation in response to stimulatory inputs, imposing a high threshold for changing behaviours. Later into mating, the timescale over which the CDNs integrate termination-promoting information expands, increasing the likelihood of switching behaviours. We suggest scalable windows of temporal integration at dedicated circuit nodes as a key but underappreciated variable in state-based decision-making.

Incremental induction of NMDAR-STP and NMDAR-LTP in the CA1 area of ventral hippocampal slices relies on graded activation of discrete NMDA receptors

N-methyl-d-aspartate receptor (NMDAR)-dependent short- and long-term types of potentiation (STP and LTP, respectively) are frequently studied in the CA1 area of dorsal hippocampal slices (DHS). Far less is known about the NMDAR dependence of STP and LTP in ventral hippocampal slices (VHS), where both types of potentiation are smaller in magnitude than in the DHS. Here, we first briefly review our knowledge about the NMDAR dependence of STP and LTP and some other forms of synaptic plasticity. We then show in new experiments that the decay of NMDAR-STP in VHS, similar to dorsal hippocampal NMDAR-STP, is not time- but activity-dependent. We also demonstrate that the induction of submaximal levels of NMDAR-STP and NMDAR-LTP in VHS differs from the induction of saturated levels of plasticity in terms of their sensitivity to subunit-preferring NMDAR antagonists. These data suggest that activation of distinct NMDAR subtypes in a population of neurons results in an incremental increase in the induction of different phases of potentiation with changing sensitivity to pharmacological agents. Differences in pharmacological sensitivity, which arise due to differences in the levels of agonist-evoked biological response, might explain the disparity of the results concerning NMDAR subunit involvement in the induction of NMDAR-dependent plasticity.This article is part of a discussion meeting issue 'Long-term potentiation: 50 years on'.

Tunable synaptic behaviors of solution-processed InGaO films for artificial visual systems

Due to their persistent photoconductivity, amorphous metal oxide thin films are promising for construction of artificial visual systems. In this work, large-scale, uniformly distributed amorphous InGaO thin films with an adjustable In/Ga ratio and thickness are prepared successfully by a low-cost environmentally friendly and easy-to-handle solution process for constructing artificial visual systems. With the increase of the In/Ga ratio and film thickness, the number of oxygen vacancies increases, along with the increase of post-synaptic current triggered by illumination, benefiting the transition of short-term plasticity to long-term plasticity. With an optimal In/Ga ratio and film thickness, the conductance response difference at a decay of 0 s between the 1st and the 10th views of a 5 × 5 array InGaO thin film transistor is up to 2.88 μA, along with an increase in the Idecay 30s/Idecay 0s ratio from 45.24% to 53.24%, resulting in a high image clarity and non-volatile artificial visual memory. Furthermore, a three-layer artificial vision network is constructed to evaluate the image recognition capability, exhibiting an accuracy of up to 91.32%. All results promise low-cost and easy-to-handle amorphous InGaO thin films for future visual information processing and image recognition.

Biomimetic Neuromorphic Sensory System via Electrolyte Gated Transistors

Biomimetic neuromorphic sensing systems, inspired by the structure and function of biological neural networks, represent a major advancement in the field of sensing technology and artificial intelligence. This review paper focuses on the development and application of electrolyte gated transistors (EGTs) as the core components (synapses and neuros) of these neuromorphic systems. EGTs offer unique advantages, including low operating voltage, high transconductance, and biocompatibility, making them ideal for integrating with sensors, interfacing with biological tissues, and mimicking neural processes. Major advances in the use of EGTs for neuromorphic sensory applications such as tactile sensors, visual neuromorphic systems, chemical neuromorphic systems, and multimode neuromorphic systems are carefully discussed. Furthermore, the challenges and future directions of the field are explored, highlighting the potential of EGT-based biomimetic systems to revolutionize neuromorphic prosthetics, robotics, and human-machine interfaces. Through a comprehensive analysis of the latest research, this review is intended to provide a detailed understanding of the current status and future prospects of biomimetic neuromorphic sensory systems via EGT sensing and integrated technologies.

Spreading Depolarization Induces a Transient Potentiation of Excitatory Synaptic Transmission

Spreading depolarization (SD) is a slowly propagating wave of prolonged activation followed by a period of synaptic suppression. Some prior reports have shown potentiation of synaptic transmission after recovery from synaptic suppression and noted similarities with the phenomenon of long-term potentiation (LTP). Since SD is increasingly recognized as participating in diverse neurological disorders, it is of interest to determine whether SD indeed leads to a generalized and sustained long-term strengthening of synaptic connections. We performed a characterization of SD-induced potentiation, and tested whether distinctive features of SD, including adenosine accumulation and swelling, contribute to reports of SD-induced plasticity. Field excitatory postsynaptic potentials (fEPSPs) were recorded in the hippocampal CA1 subregion of murine brain slices, and SD elicited using focal microinjection of KCl. A single SD was sufficient to induce a consistent potentiation of slope and amplitude of fEPSPs. Both AMPA- and NMDA-receptor mediated components were enhanced. Potentiation peaked ∼20 min after SD recovery and was sustained for ∼30 min. However, fEPSP amplitude and slope decayed over an extended 2-hour recording period and was estimated to reach baseline after ∼3 h. Potentiation was saturated after a single SD and adenosine A1 receptor activation did not mask additional potentiation. Induction of LTP with theta-burst stimulation was not altered by prior induction of SD and molecular mediators known to block LTP induction did not block SD-induced potentiation. Together, these results indicate an intermediate duration potentiation that is distinct from hippocampal LTP and may have implications for circuit function for 1-2 h following SD.

Myelin dystrophy impairs signal transmission and working memory in a multiscale model of the aging prefrontal cortex

Normal aging leads to myelin alterations in the rhesus monkey dorsolateral prefrontal cortex (dlPFC), which are positively correlated with degree of cognitive impairment. It is hypothesized that remyelination with shorter and thinner myelin sheaths partially compensates for myelin degradation, but computational modeling has not yet explored these two phenomena together systematically. Here, we used a two-pronged modeling approach to determine how age-related myelin changes affect a core cognitive function: spatial working memory. First, we built a multicompartment pyramidal neuron model fit to monkey dlPFC empirical data, with an axon including myelinated segments having paranodes, juxtaparanodes, internodes, and tight junctions. This model was used to quantify conduction velocity (CV) changes and action potential (AP) failures after demyelination and subsequent remyelination. Next, we incorporated the single neuron results into a spiking neural network model of working memory. While complete remyelination nearly recovered axonal transmission and network function to unperturbed levels, our models predict that biologically plausible levels of myelin dystrophy, if uncompensated by other factors, can account for substantial working memory impairment with aging. The present computational study unites empirical data from ultrastructure up to behavior during normal aging, and has broader implications for many demyelinating conditions, such as multiple sclerosis or schizophrenia.

Amphiphilic Interface-Mediated Ion Doping for High Performance Organic Electrochemical Transistors with Hydrophobic Polymers

An organic electrochemical transistor (OECT) is one of the promising devices for bioelectronics due to its high transconductance, encompassing low operation voltage, and good compatibility with aqueous conditions. Despite these advantages, the challenge of balancing ion penetration and electron transport remains a significant issue in OECTs. Herein, we present an amphiphilic interface modification strategy to successfully prepare OECTs in aqueous conditions based on a high-mobility hydrophobic polypyrrole derivative. An amphiphilic interface mixed with an amphiphilic polymer and the active layer markedly promotes ion penetration and results in a significant improvement in performance, with the switch time reduced from several seconds to nearly 100 ms and the transconductance increased by an order of magnitude. The high-performance OECTs fabricated by this method show promising applications in high-performance neuromorphic devices and ECG recording in advancing the field of electrochemical transistors.

A nanofluidic spiking synapse

Currently, the nanofluidic synapse can only perform basic neuromorphic pulse patterns. One immediate problem that needs to be addressed to further its capability of brain-like computing is the realization of a nanofluidic spiking device. Here, we report the use of a poly(3,4-ethylenedioxythiophene) polystyrene sulfonate membrane to achieve bionic ionic current-induced spiking. In addition to the simulation of various electrical pulse patterns, our synapse could produce transmembrane ionic current-induced spiking, which is highly analogous to biological action potentials with similar phases and excitability. Moreover, the spiking properties could be modulated by ions and neurochemicals. We expect that this work could contribute to biomimetic spiking computing in solution.

Retinal bipolar cells borrow excitability from electrically coupled inhibitory interneurons to amplify excitatory synaptic transmission

Bipolar cells of the retina carry visual information from photoreceptors in the outer retina to retinal ganglion cells (RGCs) in the inner retina. Bipolar cells express L-type voltage-gated Ca2+ channels at the synaptic terminal, but generally lack other types of channels capable of regenerative activity. As a result, the flow of information from outer to inner retina along bipolar cell processes is generally passive in nature, with no opportunity for signal boost or amplification along the way. Here we report the surprising discovery that blocking voltage-gated Na+ channels profoundly reduces the synaptic output of one class of bipolar cell, the type 6 ON bipolar cell (CBC6), despite the fact that the CBC6 itself does not express voltage-gated Na+ channels. Instead, CBC6 borrows voltage-gated Na+ channels from its neighbor, the inhibitory AII amacrine cell, with whom it is connected via an electrical synapse. Thus, an inhibitory neuron aids in amplification of an excitatory signal as it moves through the retina, ensuring that small changes in the membrane potential of bipolar cells are reliably passed onto downstream RGCs.

Parallel Synapses with Transmission Nonlinearities Enhance Neuronal Classification Capacity

Cortical neurons often establish multiple synaptic contacts with the same postsynaptic neuron. To avoid functional redundancy of these parallel synapses, it is crucial that each synapse exhibits distinct computational properties. Here we model the current to the soma contributed by each synapse as a sigmoidal transmission function of its presynaptic input, with learnable parameters such as amplitude, slope, and threshold. We evaluate the classification capacity of a neuron equipped with such nonlinear parallel synapses, and show that with a small number of parallel synapses per axon, it substantially exceeds that of the Perceptron. Furthermore, the number of correctly classified data points can increase superlinearly as the number of presynaptic axons grows. When training with an unrestricted number of parallel synapses, our model neuron can effectively implement an arbitrary aggregate transmission function for each axon, constrained only by monotonicity. Nevertheless, successful learning in the model neuron often requires only a small number of parallel synapses. We also apply these parallel synapses in a feedforward neural network trained to classify MNIST images, and show that they can increase the test accuracy. This demonstrates that multiple nonlinear synapses per input axon can substantially enhance a neuron's computational power.

Memristive Characteristics in an Asymmetrically Charged Nanochannel

The emergent nanofluidic memristor provides a promising way of emulating neuromorphic functions in the brain. The conical-shaped nanopore showed promising features for a nanofluidic memristor, inspiring us to investigate the memory effects in asymmetrically charged nanochannels due to their high current rectification, which may result in good memory effects. Here, the memory effects of an asymmetrically charged nanofluidic channel were numerically simulated by Poisson-Nernst-Planck equations. Our results showed that the I-V curves represented a diode in low scanning frequency and then became a memristor and finally a resistor as frequency increased. We successfully replicated the learning behavior in our system with history-dependent ion redistribution in the nanochannel. Some critical factors were quantitatively analyzed for the memory effects including voltage amplitude, optimal frequency, and Dukhin number. Experimental characterizations were also carried out. Our findings are useful for the design of nanofluidic memristors by the principle of enrichment and depletion as well as the determination of the best memory settings.

Altered intrinsic neural timescales and neurotransmitter activity in males with tobacco use disorder

Previous researches of tobacco use disorder (TUD) has overlooked the hierarchy of cortical functions and single modality design separated the relationship between macroscopic neuroimaging aberrance and microscopic molecular basis. At present, intrinsic timescale gradient of TUD and its molecular features are not fully understood. Our study recruited 146 male subjects, including 44 heavy smokers, 50 light smokers and 52 non-smokers, then obtained their rs-fMRI data and clinical scales related to smoking. Intrinsic neural timescale (INT) method was performed to describe how long neural information was stored in a brain region by calculating the autocorrelation function (ACF) of each voxel to examine the difference in the ability of information integration among the three groups. Then, correlation analyses were conducted to explore the relationship between INT abnormalities and clinical scales of smokers. Finally, cross-modal JuSpace toolbox was used to investigate the association between INT aberrance and the expression of specific receptor/transporters. Compared to healthy controls, TUD subjects displayed decreased INT in control network (CN), default mode network (DMN), sensorimotor areas and visual cortex, and such trend of decreasing INT was more pronounced in heavy smokers. Moreover, various neurotransmitters (including dopaminergic, acetylcholine and μ-opioid receptors) were involved in the molecular mechanism of timescale decreasing and differed in heavy and light smokers. These findings supplied novel insights into the brain functional aberrance in TUD from an intrinsic neural dynamic perspective and confirm INT was a potential neurobiological marker. And also established the connection between macroscopic imaging aberrance and microscopic molecular changes in TUD.