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This paper proposes a nanoparticle‐based atomic switch network memristive device, capable of both volatile and nonvolatile switching operations, which have not been previously reported for this material. The operational modes can be determined by altering the compliance current, demonstrating high stability over 100 cycles. Analysis of the conduction mechanism using I–V curves reveals switching characteristics consistent with space‐charge‐limited current conduction during the set process and ohmic behavior in the reset state. Furthermore, this study analyzes these dual‐operational modes in devices with varying electrode spacings. The results indicate that a wider spacing necessitated a higher compliance current for the volatile‐to‐nonvolatile transition, underscoring the significance of interconnection. These findings facilitate the integration of neuron and synapse functions within a single atomic switch network device, thereby advancing neuromorphic systems. [ABSTRACT FROM AUTHOR]

This paper presents a membrane computation error‐minimized mixed‐mode spiking neural network (SNN) crossbar array. Our approach involves implementing an embedded dummy switch scheme and a mid‐node pre‐charge scheme to construct a high‐precision current‐mode synapse. We effectively suppressed charge sharing between membrane capacitors and the parasitic capacitance of synapses that results in membrane computation error. A 400 × 20 SNN crossbar prototype chip is fabricated via a 28‐nm FDSOI CMOS process, and 20 MNIST patterns with their sizes reduced to 20 × 20 pixels are successfully recognized under 411 μW of power consumed. Moreover, the peak‐to‐peak deviation of the normalized output spike count measured from the 21 fabricated SNN prototype chips is within 16.5% from the ideal value, including sample‐wise random variations. [ABSTRACT FROM AUTHOR]

Neuromorphic computation draws inspiration from the remarkable features of the human brain including low energy consumption, parallelism, adaptivity, cognitive functions, and learning ability. These qualities hold the promise of unlocking groundbreaking computational techniques that surpass the limitations of traditional computing systems. This paper reports a remarkable photo‐synaptic behavior in the field of rare earth ion‐doped luminescent oxides by using long‐persistent luminescence (LPL). This system utilizes electron trap states to regulate the synaptic behavior, operating through a fundamentally different mechanism from that of electronic‐based synaptic devices. To realize this strategy, Tb3+ doped CaSnO3, which shows a significant LPL property under UV‐light excitation, is prepared. The luminescent system shows key neuromorphic characteristics such as paired‐pulse facilitation, pulse‐number/timing dependent potentiation, and pulse‐number/timing dependent short‐ to long‐term plasticity transition, which are required for realizing synaptic devices. This feature expands the way for advanced neuromorphic technologies employing light stimuli. [ABSTRACT FROM AUTHOR]

Photoemission spectroscopy, an experimental method based on the photoelectric effect, is now an indispensable technique used in various fields such as materials science, life science, medicine and nanotechnology. However, part of the experimental process of photoemission spectroscopy relies on experience and intuition, which is obviously a problem for novice users. In particular, photoemission spectroscopy experiments using high-brilliance synchrotron radiation as a light source are not easy for novice users because measurements must be performed quickly and accurately as scheduled within a limited experimental period. In addition, research on the application of information science methods to quantum data measurement, such as photoemission spectroscopy, is mainly aimed at the development of analysis methods, and few attempts have been made to clarify the problems faced by users who lack experience. In this study, the problems faced by novice users of photoemission spectroscopy are identified, and a native application named synapse with functions to solve these problems is implemented and evaluated qualitatively and quantitatively. This paper describes the contents of an interview survey, the functional design and the implementation of the application synapse based on the interview survey, and results and discussion of the evaluation experiment. [ABSTRACT FROM AUTHOR]

Artificial neural network‐based computing is anticipated to surpass the von Neumann bottleneck of traditional computers, thus dramatically boosting computational efficiency and showing a wide range of promising applications. In this paper, sol−gel deposition was used to prepare thin films of samarium‐doped hafnium dioxide (Sm:HfO2). When Sm is doped at a concentration of 4%, it mimics biological synapses; meantime, by voltage scanning, an obvious mimicry of resistive switching can be detected, demonstrating that the technology may be applied to simulate biological synapse characteristics, including long‐term potentiation (depression), short‐term potentiation (depression), paired‐pulse facilitation, and learning rules of spike‐time‐dependent plasticity. Additionally, a pulsed neural network is built on the MNIST dataset to test the memristor's capacity to handle visual input. The findings show the possibility of synthetic synapses in artificial intelligence systems that integrate neuromorphic computing with synaptic brain activity. [ABSTRACT FROM AUTHOR]

Artificial synapses, inspired by the intricate design of biological synapses, utilize electrical, chemical, and mechanical signals to transmit and retain information. Recent advances have involved research on artificial synapses based on organic electrochemical transistors (OECTs), emphasizing low power consumption and rapid response times. A notable challenge arises when the gate voltage is removed, causing doped ions to return quickly to the electrolyte. A simple yet efficient approach is used to solve this problem: forming a microporous active layer using a phase separation method. This technique can maximize the contact area between the electrolyte and the active layer, enhancing ion doping/de‐doping in OECTs. Improvements in the product of hole mobility and volumetric capacitance is achieved. The electrostatic coupling effect and electrochemical doping in synaptic OECTs occur better than in the pristine active layer, yielding enhanced performance with higher short‐term and long‐term synaptic plasticity, compared to pristine OECTs. Moreover, improved ambipolar characteristics is shown by n‐dopant injection. This paper reports a way to improve performance by simply modifying the surface shape of the active layer using the phase separation, contributing to advancements in artificial synapses for neural networks. [ABSTRACT FROM AUTHOR]

Copyright of Chemkon - Chemie Konkret is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Cholecystokinin (CCK) has been confirmed to be essential in NMDA‐dependent long‐term potentiation (LTP) at mouse cortical synapses. This paper has proven that CCK is necessary for LTP induced by high‐frequency stimulation of mouse hippocampal synapses projected from the entorhinal cortex. We show that the subunit of the axonal NMDA receptor dominant modulates the activity‐induced LTP by triggering pre‐synaptic CCK release. A functional pre‐synaptic NMDA receptor is required to induce LTP mediated by the axonal Ca2+ elevation and CCK exocytosis at CCK‐specific neurons. Genetic depletion of the GluN1 subunit of NMDA receptors on CCK neurons, which projected from the entorhinal cortex largely abolished the axonal Ca2+ elevation and disturbed the secretion of CCK in hippocampus. These results demonstrate that activity‐induced LTP at the hippocampal synapse is CCK‐dependent, and CCK secretion from the axonal terminal is modulated by pre‐synaptic NMDA receptors. [ABSTRACT FROM AUTHOR]

With the rapid development of artificial intelligence (AI), there is an urgent need for developing a biological sensory perception system that can simulate the human brain for information processing. Inspired by the biological vision system, photo‐responsive photonic synapses are ideal devices for constructing photosensitive artificial neural networks for neuromorphic computing tasks. This paper reports a stable photonic synaptic device in an array layout with adjustable synaptic plasticity under ultraviolet light pulses. Since the heterojunction has a photoconductivity effect and the trap layer provides superior charge carrier trapping capability, optical sensing, memory, and neuromorphic computing are integrated into a single device. Meanwhile, supervised learning of handwritten digitals is achieved by exploiting the multistate conductance by photoelectric co‐modulation and the specific decay law. The recognition rate reaches 90.6% and hardly changes with time. Additionally, the device can simplify the artificial neural network (ANN) and reduce its size to 3.78% of the original network while retaining strong fault tolerance and learning ability. The photonic artificial synapses based on ultraviolet light modulation provide a novel and effective approach for photosensory ANNs to perform in situ computation. [ABSTRACT FROM AUTHOR]

A one‐selector one resistor (1S1R) array formed of a selector and resistive random access memory (RRAM) is an important way to achieve high‐density storage and neuromorphic computing. However, the low durability and poor consistency of the selector limit its practical application. The fabrication of a selector based on egg albumen (EA) is reported in this paper. The device exhibits excellent bidirectional threshold switching characteristics, including a low leakage current (10−7 A), a high ON/OFF current ratio (106), and good endurance (>700 days). It is used as a selector to form a 1S1R unit in combination with an EA‐based RRAM to effectively solve the leakage current in a crossbar array. A feasible solution is provided for the realization of a protein‐based 1S1R array to achieve high‐density storage. The 1S1R unit shows characteristics similar to those of synapses in the human brain under impulse excitation and has great potential in simulating the human brain for neuromorphic calculations.) [ABSTRACT FROM AUTHOR]

Artificial synapses are the basic building block of artificial neural networks capable of neuromorphic computing, which might overtake conventional digital computing in areas like artificial intelligence, deep learning, and in‐memory computation. Neuromorphic computing with artificial synapses opens a new window for fast in‐memory computing and image processing. In this paper, an MoOx‐based artificial synapse that mimics almost all characteristics of bio‐synapses is demonstrated. The fabricated device shows excellent synaptic properties such as potentiation, depression, forgetting, paired‐pulse facilitation, and spike‐timing‐dependent plasticity. The mechanism behind all the observed characteristics has been well explained. A lateral‐type device is also designed and tested in order to confirm the conductance change during the application of electrical pulses. Energy‐dispersive X‐ray analysis and Raman analysis reveal that the switching mechanism is primarily due to the formation and rupture of conducting filaments composed of Magnéli phases of MoOx. Since the fabricated ITO/MoOx/Ag artificial synapse exhibits excellent synaptic characteristics and the mechanism is thoroughly explored, this study will contribute to the fabrication of neural networks and future neuromorphic computing. [ABSTRACT FROM AUTHOR]

A more accurate synaptic modeling based on oxygen vacancy conductive mechanism is presented in this paper. Two internal state variables, that is, the length and area of conductive region, are used to describe the vertical and lateral growth/dissolution dynamics of the region, based on the physical mechanisms of ion drift and two different diffusion effects. Since the effect of length on the electric field is not negligible, it is introduced into the modeling. In addition, the Fick and Soret diffusions are considered, because they cause the model to produce a "forgetting" property and a "memory" retention. By the comparisons, this modeling captures the actual device better than others. In addition, the previous models can be derived from this one. Some rough analysis suggests that the modeling possibly captures different memristors by adjusting the parameters, and the effects of oxygen concentration and temperature on synapse can also be considered. Therefore, this modeling is more comprehensive and generalized. Several important synaptic functions are simulated, including excitatory postsynaptic current, paired‐pulse facilitation, spike‐rate‐dependent plasticity, and spike‐timing‐dependent plasticity, which may provide a theoretical basis for some potential applications such as artificial neural networks and artificial intelligence. [ABSTRACT FROM AUTHOR]

Bio‐inspired artificial neural networks can be used to realize the efficient perception and parallel processing of unstructured data. This paper proposes a feedback‐controlled response system based on a NO2‐detecting artificial sensory synapse, which can process, judge, and react to a varying gas environment. The NO2‐detecting artificial sensory synapse adopts an organic heterostructure involving the charge trapping layer (pentacene) and hole‐conducting layer (copper‐phthalocyanine). The electron‐withdrawing nature of NO2 and its high compatibility with copper‐phthalocyanine induce the retentive behavior of an increase in the conductance at the hole conduction channel when consecutive positive pulses are applied to the gate terminal. The system consists of the artificial sensory synapse and artificial neuron circuits, which can provide systematic responses to varying NO2 conditions, thereby successfully simulating the efficient risk‐response system of biological neural networks. The proposed feedback‐controlled response system can facilitate the development of bionic electronics and artificial intelligence frameworks. [ABSTRACT FROM AUTHOR]

Different cellular mechanisms contribute to the hearing sense, so it is obvious that any disruption in such processes leads to hearing impairment that greatly influences the global economy and quality of life of the patients and their relatives. In the past two decades, transmembrane inner ear (TMIE) protein has received a great deal of research interest because its impairments cause hereditary deafness in humans. This evolutionarily conserved membrane protein contributes to a fundamental complex that plays role in the maintenance and function of the sensory hair cells. Although the critical roles of the TMIE in mechanoelectrical transduction or hearing procedures have been discussed, there are little to no review papers summarizing the roles of the TMIE in the auditory system. In order to fill this gap, herein, we discuss the important roles of this protein in the auditory system including its role in mechanotransduction, olivocochlear synapse, morphology and different signalling pathways; we also review the genotype-phenotype correlation that can per se show the possible roles of this protein in the auditory system. [ABSTRACT FROM AUTHOR]

A connectivity graph of neurons at the resolution of single synapses provides scientists with a tool for understanding the nervous system in health and disease. Recent advances in automatic image segmentation and synapse prediction in electron microscopy (EM) datasets of the brain have made reconstructions of neurons possible at the nanometer scale. However, automatic segmentation sometimes struggles to segment large neurons correctly, requiring human effort to proofread its output. General proofreading involves inspecting large volumes to correct segmentation errors at the pixel level, a visually intensive and time‐consuming process. This paper presents the design and implementation of an analytics framework that streamlines proofreading, focusing on connectivity‐related errors. We accomplish this with automated likely‐error detection and synapse clustering that drives the proofreading effort with highly interactive 3D visualizations. In particular, our strategy centers on proofreading the local circuit of a single cell to ensure a basic level of completeness. We demonstrate our framework's utility with a user study and report quantitative and subjective feedback from our users. Overall, users find the framework more efficient for proofreading, understanding evolving graphs, and sharing error correction strategies. [ABSTRACT FROM AUTHOR]

New Findings: What is the topic of this review? This paper overviews the links between Ca2+ and Na+ signalling in various types of cells. What advances does it highlight? This paper highlights the general importance of ionic signalling and overviews the molecular mechanisms linking Na+ and Ca2+ dynamics. In particular, the narrative focuses on the molecular physiology of plasmalemmal and mitochondrial Na+–Ca2+ exchangers and plasmalemmal transient receptor potential channels. Functional consequences of Ca2+ and Na+ signalling for co‐ordination of neuronal activity with astroglial homeostatic pathways fundamental for synaptic transmission are discussed. Abstract: Transmembrane ionic gradients, which are an indispensable feature of life, are used for generation of cytosolic ionic signals that regulate a host of cellular functions. Intracellular signalling mediated by Ca2+ and Na+ is tightly linked through several molecular pathways that generate Ca2+ and Na+ fluxes and are in turn regulated by both ions. Transient receptor potential (TRP) channels bridge endoplasmic reticulum Ca2+ release with generation of Na+ and Ca2+ currents. The plasmalemmal Na+–Ca2+ exchanger (NCX) flickers between forward and reverse mode to co‐ordinate the influx and efflux of both ions with membrane polarization and cytosolic ion concentrations. The mitochondrial calcium uniporter channel (MCU) and mitochondrial Na+–Ca2+ exchanger (NCLX) mediate Ca2+ entry into and release from this organelle and couple cytosolic Ca2+ and Na+ fluctuations with cellular energetics. Cellular Ca2+ and Na+ signalling controls numerous functional responses and, in the CNS, provides for fast regulation of astroglial homeostatic cascades that are crucial for maintenance of synaptic transmission. [ABSTRACT FROM AUTHOR]

A half century after Ray Guillery's classic descriptions of cell types, axon types, and synaptic architecture of the dorsal lateral geniculate nucleus, the functional organization of this nucleus, as well as all other thalamic nuclei, is still of enormous interest. This review will focus on two classic papers written by Ray Guillery: 'A study of Golgi preparations from the dorsal lateral geniculate nucleus of the adult cat', and 'The organization of synaptic interconnections in the laminae of the dorsal lateral geniculate nucleus of the cat', as well as the studies that most directly followed from the insights these landmark manuscripts provided. It is hoped that this review will honor Ray Guillery by encouraging further investigations of the synaptic organization of the dorsal thalamus., (© 2018 Federation of European Neuroscience Societies and John Wiley & Sons Ltd.)

Transition metal carbides, called MXenes, can be used for MXene‐based unique electronic devices such as new types of batteries, energy storage devices, and supercapacitors, where MXene is used as an electrode. The unique surface properties of MXene and 2D structure can be further applied to the new electronic devices. In this paper, the unique insulating properties of partially oxidized MXene (Ti3C2Tx) sheets are utilized for memory storage and electronic synapse applications. The device exhibits threshold resistive switching characteristics based on Ag+ migration dynamics. It is found that this Ag+ cation migration is similar to Ca2+ ion dynamics of a biological synapse, and thus, biological synapse functions such as intrusion/extrusion of Ag+ cation, paired‐pulse facilitation (PPF), post‐tetanic potentiation (PTP), short‐term potentiation (STP), and transition of STP to long‐term potentiation (LTP) are well‐emulated. It is believed that this device development can be potentially used in the next‐generation hardware‐based artificial intelligence systems. [ABSTRACT FROM AUTHOR]

In this paper, a model of the neuron based on the dendrite mechanism is proposed. The neuron model takes the form of a dendrite, and the interaction between synapses and so on, which are not considered by the conventional model, is taken into account. In this paper, the form of a dendrite is assumed to be arbitrary and interaction is assumed to exist among all synapses. That is, a superfluous synapse is formed, and is expressed in a logical network, then the equivalence between them is shown. The ripened dendrite is formed during learning by screening unnecessary dendrites, and strengthening and fixing the useful dendrites. The model proposed in this paper can correspond to the linearly unseparated problem, unlike the one-layer traditional neuron. Moreover, learning of this model suggests the form of the dendrites and the positions of the excitation and inhibition synapses. This may give some very useful suggestions for biologists. © 2001 Scripta Technica, Electron Comm Jpn Pt 3, 84(8): 11–24, 2001 [ABSTRACT FROM AUTHOR]

Physiologically based models could facilitate better understanding of mechanisms underlying epileptic seizures. In this paper, we attempt to reveal the dynamic evolution of intracranial EEG activity during epileptic seizures based on synaptic gain identification procedure of a neural mass model. The distribution of average excitatory, slow and fast inhibitory synaptic gain in the parameter space and their temporal evolution, i.e., the path through the model parameter space, were analyzed in thirty seizures from ten temporal lobe epileptic patients. Results showed that the synaptic gain values located roughly on a plane before seizure onset, dispersed during seizure and returned to the plane when seizure terminated. Cluster analysis was performed on seizure paths and demonstrated consistency in synaptic gain evolution across different seizures from the individual patient. Furthermore, two patient groups were identified, each one corresponding to a specific synaptic gain evolution in the parameter space during a seizure. Results were validated by a bootstrapping approach based on comparison with random paths. The differences in the path revealed variations in EEG dynamics for patients despite showing identical seizure onset pattern. Our approach may have the potential to classify the epileptic patients into subgroups based on different mechanisms revealed by subtle changes in synaptic gains and further enable more robust decisions regarding treatment strategy., (© 2018 Federation of European Neuroscience Societies and John Wiley & Sons Ltd.)

Synaptic transmission is the mechanism of information transfer from one neuron to another (or from a neuron to a muscle or to an endocrine cell). An important step in this physiological process is the stochastic release of neurotransmitter from vesicles that fuse with the presynaptic membrane and spill their contents into the synaptic cleft. We are concerned here with the formulation, analysis, and simulation of a mathematical model that describes the stochastic docking, undocking, and release of synaptic vesicles and their effect on synaptic signal transmission. The focus of this paper is on the parameter p0, the probability of release for each docked vesicle when an action potential arrives. We study the influence of this parameter on the statistics of the release process and on the theoretical capability of the model synapse in reconstructing various desired outputs based on the timing and amount of neurotransmitter release. This theoretical capability is assessed by formulating and solving an optimal filtering problem. Methods for parameter identification are proposed and applied to simulated data. © 2019 Wiley Periodicals, Inc. [ABSTRACT FROM AUTHOR]

The objective of this paper was to collect normative data essential for analyzing the subplate (SP) role in pathogenesis of developmental disorders, characterized by abnormal circuitry, such as hypoxic‐ischemic lesions, autism and schizophrenia. The main cytological features of the SP, such as low cell density, early differentiation of neurons and glia, plexiform arrangement of axons and dendrites, presence of synapses and a large amount of extracellular matrix (ECM) distinguish this compartment from the cell‐dense cortical plate (CP; towards pia) and large fiber bundles of external axonal strata of fetal white matter (towards ventricle). For SP delineation from these adjacent layers based on combined cytological criteria, we analyzed the sublaminar distribution of different microstructural elements and the associated maturational gradients throughout development, using immunocytochemical and histological techniques on postmortem brain material (Zagreb Neuroembryological Collection). The analysis revealed that the SP compartment of the lateral neocortex shows changes in laminar organization throughout fetal development: the monolayer in the early fetal period (presubplate) undergoes dramatic bilaminar transformation between 13 and 15 postconceptional weeks (PCW), followed by subtle sublamination in three 'floors' (deep, intermediate, superficial) of midgestation (15–21 PCW). During the stationary phase (22–28 PCW), SP persists as a trilaminar compartment, gradually losing its sublaminar organization towards the end of gestation and remains as a single layer of SP remnant in the newborn brain. Based on these sublaminar transformations, we have documented developmental changes in the distribution, maturational gradients and expression of molecular markers in SP synapses, transitional forms of astroglia, neurons and ECM, which occur concomitantly with the ingrowth of thalamo‐cortical, basal forebrain and cortico‐cortical axons in a deep to superficial fashion. The deep SP is the zone of ingrowing axons – 'entrance (ingrowth) zone'. The process of axonal ingrowth begins with thalamo‐cortical fibers and basal forebrain afferents, indicating an oblique geometry. During the later fetal period, deep SP receives long cortico‐cortical axons exhibiting a tangential geometry. Intermediate SP ('proper') is the navigation and 'nexus' sublamina consisting of a plexiform arrangement of cellular elements providing guidance and substrate for axonal growth, and also containing transient connectivity of dendrites and axons in a tangential plane without radial boundaries immersed in an ECM‐rich continuum. Superficial SP is the axonal accumulation ('waiting compartment') and target selection zone, indicating a dense distribution of synaptic markers, accumulation of thalamo‐cortical axons (around 20 PCW), overlapping with dendrites from layer VI neurons. In the late preterm brain period, superficial SP contains a chondroitin sulfate non‐immunoreactive band. The developmental dynamics for the distribution of neuronal, glial and ECM markers comply with sequential ingrowth of afferents in three levels of SP: ECM and synaptic markers shift from deep to superficial SP, with transient forms of glia following this arrangement, and calretinin neurons are concentrated in the SP during the formation phase. These results indicate developmental and morphogenetic roles in the SP cellular (transient glia, neurons and synapses) and ECM framework, enabling the spatial accommodation, navigation and establishment of numerous connections of cortical pathways in the expanded human brain. The original findings of early developmental dynamics of transitional subtypes of astroglia, calretinin neurons, ECM and synaptic markers presented in the SP are interesting in the light of recent concepts concerning its functional and morphogenetic role and an increasing interest in SP as a prospective substrate of abnormalities in cortical circuitry, leading to a cognitive deficit in different neurodevelopmental disorders. [ABSTRACT FROM AUTHOR]

GLO:80N/15apr21:ejn14704-toc-0001.jpg PHOTO (COLOR): . gl GLO:80N/15apr21:ejn14704-fig-0001.jpg PHOTO (COLOR): . gl It is our pleasure to introduce Dr. Marisela Morales, the next investigator for the series "Profiles of Women In Science" (Helmreich, Bolam & Foxe, 2017). Dr. Morales is the Branch Chief of the Integrative Neuroscience Research Branch at the National Institute on Drug Abuse (NIDA). [Extracted from the article]

Presently described is a sliding‐kernel computation‐in‐memory (SKCIM) architecture conceptually involving two overlapping layers of functional arrays, one containing memory elements and artificial synapses for neuromorphic computation, the other is used for storing and sliding convolutional kernel matrices. A low‐temperature metal‐oxide thin‐film transistor (TFT) technology capable of monolithically integrating single‐gate TFTs, dual‐gate TFTs, and memory capacitors is deployed for the construction of a physical SKCIM system. Exhibiting an 88% reduction in memory access operations compared to state‐of‐the‐art systems, a 32 × 32 SKCIM system is applied to execute common convolution tasks. A more involved demonstration is the application of a 5‐layer, SKCIM‐based convolutional neural network to the classification of the modified national institute of standards and technology (MNIST) dataset of handwritten numerals, achieving an accuracy rate of over 95%. [ABSTRACT FROM AUTHOR]

Copyright of Experimental Physiology is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

In the correlation-type associative memory model it is known that the storage capacity per synapse increases when synapses are pruned. In that case, however, the storage capacity of the whole network is decreased. In order to solve this difficulty, the authors introduce the synapse with delay, and propose a scheme in which the coupling rate of the synapse is reduced while retaining the number of synapses. As an example of such an approach, this paper discusses a discrete-time synchronous model with delayed coupling and synaptic pruning. The dynamics of the model is investigated theoretically by statistical neurodynamics, and the storage capacity is analyzed quantitatively. An analysis is performed for two types of synaptic pruning, random and systematic. In either case, it is seen that the storage capacity increases when the number of delay stages is increased while reducing the synaptic coupling rate, provided that the total number of synapses is kept constant. The increasing tendency is more marked in systematic pruning than in random pruning. These results were verified by comparing the results to those of computer simulation. The significance of the theoretical findings and the excessive generation and pruning of the synapses in the brain are also discussed from the viewpoint of the theory of computation. © 2003 Wiley Periodicals, Inc. Electron Comm Jpn Pt 3, 86(6): 48–58, 2003; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/ecjc.10037 [ABSTRACT FROM AUTHOR]

When activated, metabotropic glutamate receptors (mGlus) exert long-lasting changes within the glutamatergic synapses. One mechanism is a tonic effect of downstream signal transduction pathways via sustained activation of mGlu itself. Like many other G protein-coupled receptors (GPCRs), mGlu can exist in a constitutively active state, which persists agonist independently. In this paper, we review the current knowledge of the mechanisms underlying the constitutive activity of group I mGlus. The issues concerning Homer1a mechanism in the constitutive activity of group I mGlus and recent findings regarding the significant role of β-arrestin in sustained GPCR activity are also discussed. We propose that once in a state of sustained activation, the mGlu persistently activates downstream signaling pathways, including various adaptor proteins and kinases, such as β-arrestin and mitogen-activated protein kinases. In turn, these effector molecules bind to or phosphorylate the mGlu C-terminal binding domains and consequently regulate the activation state of the mGlu. [ABSTRACT FROM AUTHOR]

The search for memory is one of the oldest quests in written human history. For at least two millennia, we have tried to understand how we learn and remember. We have gradually converged on the brain and looked inside it to find the basis of knowledge, the trace of memory. The search for memory has been conducted on multiple levels, from the organ to the cell to the synapse, and has been distributed across disciplines with less chronological or intellectual overlap than one might hope. Frequently, the study of the mind and its memories has been severely restricted by technological or philosophical limitations. However, in the last few years, certain technologies have emerged, offering new routes of inquiry into the basis of memory. The 2016 Kavli Futures Symposium was devoted to the past and future of memory studies. At the workshop, participants evaluated the logic and data underlying the existing and emerging theories of memory. In this paper, written in the spirit of the workshop, we briefly review the history of the hunt for memory, summarizing some of the key debates at each level of spatial resolution. We then discuss the exciting new opportunities to unravel the mystery of memory. [ABSTRACT FROM AUTHOR]

Bioinspired synaptic devices have shown great potential in artificial intelligence and neuromorphic electronics. Low energy consumption, multi‐modal sensing and recording, and multifunctional integration are critical aspects limiting their applications. Recently, a new synaptic device architecture, the ion‐gating vertical transistor (IGVT), has been successfully realized and timely applied to perform brain‐like perception, such as artificial vision, touch, taste, and hearing. In this short time, IGVTs have already achieved faster data processing speeds and more promising memory capabilities than many conventional neuromorphic devices, even while operating at lower voltages and consuming less power. This work focuses on the cutting‐edge progress of IGVT technology, from outstanding fabrication strategies to the design and realization of low‐voltage multi‐sensing IGVTs for artificial‐synapse applications. The fundamental concepts of artificial synaptic IGVTs, such as signal processing, transduction, plasticity, and multi‐stimulus perception are discussed comprehensively. The contribution draws special attention to the development and optimization of multi‐modal flexible sensor technologies and presents a roadmap for future high‐end theoretical and experimental advancements in neuromorphic research that are mostly achievable by the synaptic IGVTs. [ABSTRACT FROM AUTHOR]

This paper argues that there is a revolution afoot in the developmental science of gene-environment interplay. We summarize, for an audience of developmental researchers and clinicians, how epigenetic processes - chromatin structural modifications that regulate gene expression without changing DNA sequences - may offer a strong, parsimonious account for the convergence of genetic and contextual variation in the genesis of adaptive and maladaptive development. Epigenetic processes may play a plausible explanatory role in understanding: divergent trajectories and sexual dimorphisms in brain development; statistical interactions between genes and environments; the biological embedding of early psychosocial adversities; the linkages of such adversities to disorders of mental health; the striking individual variation in the strength of those linkages; the molecular origins of critical and sensitive periods; and the transgenerational inheritance of risk and protection. Taken together, these arguments converge in a claim that epigenetic processes constitute a promising and illuminating point of connection - a 'synapse' - between genes and environments., (© 2014 John Wiley & Sons Ltd.)

The development of new antidepressants has had mixed results over the past decade, with several notable failures. This paper reviews a number of major initiatives in the development of new antidepressant agents. Traditional strategies to build on agents that have monoaminergic effects at the synapse (e.g., vilazodone and ketamine) have been complemented with efforts that have emphasized devices and brain circuits (e.g., deep brain stimulation and transcranial magnetic stimulation) or chemical agents that modulate neuroendocrine systems (e.g., glucocorticoid antagonists, mixed melatonin agonists/serotonin type-2 receptor antagonists). Interestingly, chemical agents, such as onabotulinumtoxin A, may affect brain circuits as well. We present data from recent studies in drug and device development--reviewing progress made, stumbling blocks encountered, and issues that need to be addressed in future studies. [ABSTRACT FROM AUTHOR]

Two‐dimensional (2D) ferroionics is appealing in performing complex artificial intelligence tasks due to the interesting property of coexistence of ferroelectricity and ionic activities. CuInP2S6 (CIPS), as a typical 2D ferroionic material, is highly conducive to rich functions of information devices due to the displacement of Cu+ inducing both ferroelectricity and ionic conductivity. However, the coupling and modulation of polarization and ion migration in CIPS for multifunctional information devices has not been fully explored. Here, this study demonstrates that digital memory and synaptic simulations are realized in Au/CIPS/Au device via engineering ferroelectric polarization reversal and the long‐distance migration of the Cu+ to change conductive modes. Steep resistive switching behavior based on ion‐migration is observed with a high on/off ratio of over 108, long retention time (>2 × 104 s), and current compliance engineered multilevel resistance states, demonstrating reliable nonvolatile high‐density memory characteristics. Based on the continuous modulation of polar order, the key synaptic behaviors are successfully simulated. Moreover, by the co‐modulation of polarization state and ions migration, the paired‐pulse facilitation, paired‐pulse depression, and potentiation following depression are achieved. These results suggest that CIPS is a promising candidate for constructing high‐performance, function‐enriched devices for data storage, information processing, and neuromorphic computing. [ABSTRACT FROM AUTHOR]

Entering the era of AI 2.0, bio‐inspired target recognition facilitates life. However, target recognition may suffer from some risks when the target is hijacked. Therefore, it is significantly important to provide an encryption process prior to neuromorphic computing. In this work, enlightened from time‐varied synaptic rule, an in‐memory asymmetric encryption as pre‐authentication is utilized with subsequent convolutional neural network (ConvNet) for target recognition, achieving in‐memory two‐factor authentication (IM‐2FA). The unipolar self‐oscillated synaptic behavior is adopted to function as in‐memory asymmetric encryption, which can greatly decrease the complexity of the peripheral circuit compared to bipolar stimulation. Results show that without passing the encryption process with suitable weights at the correct time, the ConvNet for target recognition will not work properly with an extremely low accuracy lower than 0.86%, thus effectively blocking out the potential risks of involuntary access. When a set of correct weights is evolved at a suitable time, a recognition rate as high as 99.82% can be implemented for target recognition, which verifies the effectiveness of the IM‐2FA strategy. [ABSTRACT FROM AUTHOR]

Stochasticity plays a significant role in the low‐power operation of a biological neural network. In an artificial neural network, stochasticity also contributes to critical functions such as the uncertainty quantification (UQ) for estimating the probability for the correctness of prediction. This UQ is vital for cutting‐edge applications, including medical diagnostics, autopilots, and large language models. Thanks to nonlinear variation of analogous Hall resistance with high computing velocity and low dissipation, a stochastic spin‐orbit‐torque (SOT) device exhibits significant potential for implementing the UQ. However, up until now, the application of UQ for stochastic SOT devices remains unexplored. In this study, based on SOT‐induced stochastic magnetic domain wall (DW) motion with varying velocity, a SOT synapse is fabricated that can emulate stochastic weight update following the Spike‐Timing‐Dependent‐Plasticity (STDP) rule. Furthermore, a stochastic SNN is set up, which, when compared to its deterministic counterpart, demonstrates a clear advantage in quantifying uncertainty for diagnosing the type of breast tumor (benign or malignant). [ABSTRACT FROM AUTHOR]

The realization of artificial synapses based on biomaterials is of great significance for the development of environmentally friendly neuromorphic hardware systems and artificial intelligence. In this sense, a bioartificial synapse composited with egg albumen (EA) and multiwalled carbon nanotubes (MWCNTs) is fabricated. Based on the adjustable weight of the artificial synapse, the plasticity of electrical synapses is explored. Due to the photogenerated carriers and thermoelectric effects of carbon nanotubes, the device has optoelectronic properties, so the optoelectronic synaptic plasticity of the device is explored under light pulses. The device is well suited for biological synapses and shows great potential for applications in future high‐density storage and neuromorphic computing systems. In addition, to further study the physical mechanism of the conductive process of the device, the electrical characteristics of the contact interface between carbon nanotubes doped with Fe substitution and the upper electrode Al are mainly analyzed by first principles, and the adsorption, charge distribution, and band structure between them are theoretically studied. [ABSTRACT FROM AUTHOR]

Hybrid perovskites have attracted enormous attention in the next generation resistive switching (RS) memristor for the artificial synapses, owing to their ambipolar charge transport, long diffusion length, and tunable visible bandgap. However, the variable switch, limited reproducibility, and poor endurance are the obstacles to the practical application of the perovskite memristors. Herein, we reported a multilevel RS nonvolatile memory based on a 3D trigonal HC(NH2)2PbI3 (α‐FAPbI3) perovskite layer modified by 1‐cyanobutyl‐3‐methylimidazolium chloride ([CNBmim]Cl) and sandwiched between ITO and Au electrodes (Au/[CNBmim]Cl/α‐FAPbI3/SnO2/ITO). In contrast to the bare memristor with failure switching from low resistance state (LRS) to high resistance state (HRS), the memristor device based on the α‐FAPbI3 modified with [CNBmim]Cl (Target device) shows the retention time over 104 s with On/Off ratio (>102) and endurance up to 550 cycles. The stable RS cycle benefits from the accelerated electrons de‐trapping from the reduced defects and fast charge separation in the interface of α‐FAPbI3/electrode, leading to the rupture of conductive filaments and transition of LRS to HRS. As a two‐terminal analog synaptic device, the target device can realize random handwritten digit recognition with an impressive accuracy of 89.3% on the condition of low learning phases (500 training cycles). [ABSTRACT FROM AUTHOR]

Memristive devices such as resistive switching memories and artificial synapses have emerged as promising technologies to overcome the technological challenges associated with the von Neumann bottleneck. Recently, lead halide perovskites have drawn substantial research attention as the candidate material for memristors and artificial synapses due to their unique optoelectronic properties, solution processability, and mechanical flexibility. However, the toxicity of lead‐containing species has raised major concerns for health and the environment, which makes it crucial to transition from lead‐based to lead‐free materials for practical applications. Herein, the recent progress of lead‐free metal halides including perovskites and perovskite analogs for resistive memory and artificial synapse is reviewed. Initially, the fundamentals of lead‐free materials and switching mechanisms are introduced. Next, the material design, fabrication technique, and device performance are summarized and critically evaluated for each metal halide species. Finally, the challenges of the lead‐free metal halides toward memristors and artificial synapses are outlined and discussed, and some potential research directions for future study are proposed. [ABSTRACT FROM AUTHOR]

Dynamic doping by electrochemical ion intercalation is a promising mechanism for modulating electronic conductivity, allowing for energy‐efficient, brain‐inspired computing hardware. While proton‐based devices have achieved success in terms of speed and efficiency, the volatility and environmental pervasiveness of hydrogen (H) might limit the robustness of devices during fabrication, as well as the long‐term retention of devices after programming. This motivates the search for alternative working ions. In this work, a proof‐of‐concept is demonstrated for electrochemical ionic synapses (EIS) based on intercalation of Mg2+ ions. The reported device has a symmetric design, with MgxWO3 used as both the gate and channel material. Increasing the Mg fraction, x, in WO3 increases the electronic conductance in a continuum over a large range (80 nS − 2 mS). Ex situ characterization of the channel confirms that modulation of channel conductance is due to Mg2+ intercalation. Unlike H‐EIS which rapidly loses programmed conductance states over a few seconds when exposed to air, Mg‐EIS can be operated and has good retention in air, with no sign of degradation after 1 h. Mg2+ as a working ion with WO3 as the channel is a promising material system for EIS with long‐term retention and low energy consumption. [ABSTRACT FROM AUTHOR]

The prevalence of artificial intelligence applications using artificial neural network architectures for functions such as natural language processing, text prediction, object detection, speech, and image recognition has significantly increased in today's world. The computational functions performed by artificial neural networks in classical applications require intensive and large‐scale data movement between memory and processing units. Various software and hardware efforts are being made to perform these operations more efficiently. Despite these efforts, latency in data traffic and the substantial amount of energy consumed in data processing emerge as bottleneck disadvantages of the Von Neumann architecture. To overcome this bottleneck problem, it is necessary to develop hardware units specific to artificial intelligence applications. For this purpose, neuro‐inspired computing chips are believed to provide an effective approach by designing and integrating a set of features inspired by neurobiological systems at the hardware level to address the problems arising in artificial intelligence applications. The most notable among these approaches is memristor‐based neuromorphic computing systems. Memristors are seen as promising devices for hardware‐level improvement in terms of speed and energy because they possess non‐volatile memory and exhibit analog behavior. They enable effective storage and processing of synaptic weights, offering solutions for hardware‐level development. Taking into account these advantages of memristors, this study examines the research conducted on artificial neural networks and hardware that can directly perform deep learning functions and mimic the biological brain, which is different from classical systems in today's context. [ABSTRACT FROM AUTHOR]

Transferring the concept of chemical‐driven responses into artificial intelligence technology holds the key to mimicking olfactory for neuromorphic computing of chemical recognition. Currently, artificial olfactory systems are designed based on chemical sensor arrays. Time‐dependent responses of the sensor arrays are processed by artificial neural networks for recognition. However, the sensors generate instantly volatile responses, and algorithms for the processing of the time‐dependent responses have not been involved. The recognition accuracy and speed are severely impeded. A sensor array can only achieve an accuracy of 90% after at least 5 training epochs. Herein an artificial olfactory chemical‐resistant synapse consisting of 3D hierarchical WO3@WO3 nanofibers are demonstrated. The nanofibers exhibit persistent resistance responses through chemical exposures due to the strong chemisorption of water molecules. Typical synaptic behaviors including paired‐pulse facilitation, long‐term −1 short‐term memory, and learning experience have been achieved. Next, a recurrent neural network that is committed to processing the time‐dependent data is used to identify gas‐phase chemicals of 3‐hydroxy‐2‐butanone, triethylamine, and trimethylamine. Training‐free gas recognition has been realized by a WO3@WO3 nanofiber synapse only, in which the accuracy is above 90% at the first epoch. The results have great potential to satisfy stringent performance requirements on artificial perception systems. [ABSTRACT FROM AUTHOR]

Rhythmic biological functions in mammals are orchestrated by a circadian timekeeper in the suprachiasmatic nucleus of the hypothalamus (SCN) which precisely adjusts clock outputs to solar time through the process of photic synchronization. Entrainment to the 24-h light-dark cycle is known to act on the molecular loops which trigger circadian oscillations but is also thought to involve day-night adjustments in the intercellular phasing of the multiple component SCN oscillators. This view is supported by data showing that the SCN undergoes important rearrangements of its neuroglial architecture throughout the 24-h cycle. The present paper highlights our data showing in rat that the two main sources of SCN efferents, composed of neurons synthesizing either vasopressin (AVP) or vasoactive intestinal peptide (VIP), are differentially involved in day-night SCN neuroglial plasticity. We found that the synaptic inputs received by the VIP neurons, which are major integrators of photic signals in the retinorecipient SCN subregion, increased during the day while those received by the AVP neurons remained unchanged at day and night. Glutamatergic axons, known to convey photic information from the retina, together with nonglutamatergic axons, contribute to the synaptic remodellings on VIP neurons. Experimental data providing strong indication that these plastic events may subserve synchronization of the clock to the light-dark cycle and that the daily fluctuations of plasma glucocorticoid hormones may act as temporal endocrine signals that may modulate SCN neuroglial plasticity through the rhythmic release of serotonin are also reviewed., (© 2010 The Authors. European Journal of Neuroscience © 2010 Federation of European Neuroscience Societies and Blackwell Publishing Ltd.)

What is the biological basis for human cognition? Our understanding why human brains make us smarter than other animals is still in its infancy. In recent years, astrocytes have been shown to be indispensable for neuronal survival, growth, synapse formation, and synapse function. Now, in a new study from Maiken Nedergaard and Steven Goldman's groups (Han et al., 2013), human glia progenitor cells have been transplanted into mouse forebrains. These progenitors survived, migrated widely, and gave rise to astrocytes that displayed the characteristics of human astrocytes in the rodent host brains. Strikingly, the mice with transplanted human cells displayed improved long term potentiation (LTP) and learning, suggesting the potential importance of human astrocytes in the unique cognitive abilities of human brains. This landmark paper is an important first step toward future investigations of whether and how human astrocytes play a role in distinguishing the cognitive abilities of humans from those of other animals. [ABSTRACT FROM AUTHOR]

CA1 pyramidal neurons of the hippocampus express various types of serotonin (5-HT) receptors, such as 5-HT(1A), 5-HT(4) and 5-HT(7) receptors, which couple to Galpha(i) or Galpha(s) proteins and operate on different intracellular signalling pathways. In the present paper we verify such differential serotonergic modulation for the hyperpolarization-activated current I(h). Activation of 5-HT(1A) receptors induced an augmentation of current-induced hyperpolarization responses, while the responses declined after 5-HT(4) receptors were activated. The resting potential of neurons hyperpolarized (-2.3 +/- 0.7 mV) after 5-HT(1A) receptor activation, activation of 5-HT(4) receptors depolarized neurons (+3.3 +/- 1.4 mV). Direct activation of adenylyl cyclase (AC) by forskolin also produced a depolarization. In voltage clamp, the Ih current was identified by its characteristic voltage- and time-dependency and by blockade with CsCl or ZD7288. Activation of 5-HT(1A) receptors reduced I(h) and shifted the activation curve to a more negative voltage by -5 mV at half-maximal activation. Activation of 5-HT(4) and 5-HT(7) receptors increased I(h) and shifted the activation curve to the right by +5 mV. Specific activation of 5-HT(4) receptors by BIMU8 increased membrane conductance and showed an increase in I(h) in a subset of cells, but did not induce a significant alteration in the activation curve. In order to verify spatial differences, we applied BIMU8 selectively to the soma and to the dendrites. Only somatic application induced receptor activation. These data are confirmed by immunofluorescence stainings with an antibody against the 5-HT(4) receptor, revealing receptor expression at the somata of the CA1 region. A similar expression pattern was found with a new antibody against 5-HT(7) receptors which reveals immunofluorescence staining on the cell bodies of pyramidal neurons.

The human brain is made up of an extensive network of neurons that communicate by forming specialized connections called synapses. The amount, location, and dynamic turnover of synaptic proteins, including neurotransmitter receptors and synaptic scaffolding molecules, are under complex regulation and play a crucial role in synaptic connectivity and plasticity, as well as in higher brain functions. An increasing number of studies have established ubiquitination and proteasome-mediated degradation as universal mechanisms in the control of synaptic protein homeostasis. In this paper, we focus on the role of the ubiquitin-proteasome system(UPS) in the turnover of major neurotransmitter receptors, including glutamatergic and nonglutamatergic receptors, as well as postsynaptic receptor-interacting proteins. [ABSTRACT FROM AUTHOR]

HIV-1 particle assembly is driven by the structural protein Gag. Gag binds to and multimerizes on the inner leaflet of the plasma membrane, eventually resulting in formation of spherical particles. During virus spread among T cells, Gag accumulates to the plasma membrane domain that, together with target cell membrane, forms a cell junction known as the virological synapse. While Gag association with plasma membrane microdomains has been implicated in virus assembly and cell-to-cell transmission, recent studies suggest that, rather than merely accumulating to pre-existing microdomains, Gag plays an active role in reorganizing the microdomains via its multimerization activity. In this paper, we will discuss this emerging view of Gag microdomain interactions. Relationships between Gag multimerization and microdomain association will be further discussed in the context of Gag localization to T-cell uropods and virological synapses. [ABSTRACT FROM AUTHOR]

Synapse formation is considered to be crucial for learning and memory. Understanding the underlying molecular mechanisms of synapse formation is a key to understanding learning and memory. Kalirin-7, a major isoform of Kalirin in adult rodent brain, is an essential component of mature excitatory synapses. Kalirin-7 interacts with multiple PDZ-domain-containing proteins including PSD95, spinophilin, and GluR1 through its PDZ-binding motif. In cultured hippocampal/cortical neurons, overexpression of Kalirin-7 increases spine density and spine size whereas reduction of endogenous Kalirin-7 expression decreases synapse number, and spine density. In Kalirin-7 knockout mice, spine length, synapse number, and postsynaptic density (PSD) size are decreased in hippocampal CA1 pyramidal neurons; these morphological alterations are accompanied by a deficiency in long-term potentiation (LTP) and a decreased spontaneous excitatory postsynaptic current (sEPSC) frequency. Human Kalirin-7, also known as Duo or Huntingtin-associated protein-interacting protein (HAPIP), is equivalent to rat Kalirin-7. Recent studies show that Kalirin is relevant to many human diseases such as Huntington's Disease, Alzheimer's Disease, ischemic stroke, schizophrenia, depression, and cocaine addiction. This paper summarizes our recent understanding of Kalirin function. [ABSTRACT FROM AUTHOR]

A growing body of research indicates a pivotal role for astrocytes at the developing synapse. In particular, astrocytes are dynamically involved in governing synapse structure, function, and plasticity. In the postnatal brain, their appearance at synapses coincides with periods of developmental plasticity when neural circuits are refined and established. Alterations in the partnership between astrocytes and neurons have now emerged as important mechanisms that underlie neuropathology. With overall synaptic function standing as a prominent link to the expression of the disease phenotype in a number of neuro developmental disorders and knowing that astrocytes influence synapse development and function, this paper highlights the current knowledge of astrocyte biology with a focus on their involvement in fragile X syndrome. [ABSTRACT FROM AUTHOR]

During cortical development, proliferating neural progenitors exhibit polarized apical and basolateral membranes that are maintained by tightly controlled and membrane-specific vesicular trafficking pathways. Disruption of polarity through impaired delivery of proteins can alter cell fate decisions and consequent expansion of the progenitor pool, as well as impact the integrity of the neuroependymal lining. Loss of neuroependymal integrity disrupts radial glial scaffolding and alters initial neuronal migration from the ventricular zone. Vesicle trafficking is also required for maintenance of lipid and protein cycling within the leading and trailing edge of migratory neurons, as well as dendrites and synapses of mature neurons. Defects in this transport machinery disrupt neuronal identity, migration, and connectivity and give rise to a malformation of cortical development termed as periventricular heterotopia (PH). PH is characterized by a reduction in brain size, ectopic clusters of neurons localized along the lateral ventricle, and epilepsy and dyslexia. These anatomical anomalies correlate with developmental impairments in neural progenitor proliferation and specification, migration from loss of neuroependymal integrity and neuronal motility, and aberrant neuronal process extension. Genes causal for PH regulate vesicle-mediated endocytosis along an actin cytoskeletal network. This paper explores the role of these dynamic processes in cortical development and disease. [ABSTRACT FROM AUTHOR]

Establishing novel episodic memories and stable spatial representations depends on an exquisitely choreographed, multistage process involving the online encoding and offline consolidation of sensory information, a process that is largely dependent on the hippocampus. Each step is influenced by distinct neural network states that influence the pattern of activation across cellular assemblies. In recent years, the occurrence of hippocampal sharp wave ripple (SWR) oscillations has emerged as a potentially vital network phenomenon mediating the steps between encoding and consolidation, both at a cellular and network level by promoting the rapid replay and reactivation of recent activity patterns. Such events facilitate memory formation by optimising the conditions for synaptic plasticity to occur between contingent neural elements. In this paper, we explore the ways in which SWRs and other network events can bridge the gap between spatiomnemonic processing at cellular/synaptic and network levels in the hippocampus. [ABSTRACT FROM AUTHOR]