A new type artificial synapse based on the organic copolymer memcapacitor

All-in-one metal-oxide heterojunction artificial synapses for visual sensory and neuromorphic computing systems

Various hippocampal and neocortical synapses of mammalian brain show both short-term plasticity and long-term plasticity, which are considered to underlie learning and memory by the brain. According to Hebb’s postulate, synaptic plasticity encodes memory traces of past experiences into cell assemblies in cortical circuits. However, it remains unclear how the various forms of long-term and short-term synaptic plasticity cooperatively create and reorganize such cell assemblies. Here, we investigate the mechanism in which the three forms of synaptic plasticity known in cortical circuits, i.e., spike-timing-dependent plasticity (STDP), short-term depression (STD) and homeostatic plasticity, cooperatively generate, retain and reorganize cell assemblies in a recurrent neuronal network model. We show that multiple cell assemblies generated by external stimuli can survive noisy spontaneous network activity for an adequate range of the strength of STD. Furthermore, our model predicts that a symmetric temporal window of STDP, such as observed in dopaminergic modulations on hippocampal neurons, is crucial for the retention and integration of multiple cell assemblies. These results may have implications for the understanding of cortical memory processes.

Ultrasensitive artificial synapse based on conjugated polyelectrolyte

From early age in the human brain occurs plasticity process that influences its development. The functioning of the brain is governed by its neuronal connectivity and the synaptic dynamics of these connections. A neuron, over thousands of synapses, can receive a large number of inputs and produce different outputs leading to the consolidation and integration of memory. Synaptic plasticity is the set of experience-dependent changes in neuronal pathways that support acquired habits. It is the ability of the nervous system to reshape connectivity between neurons, changing the functional and structural organization of neuronal circuits that allows us to adapt to the multiple and continuous changes in the environment and leading to processes such as cognitive development and the ability to learn. Synaptic plasticity is mainly due to short- and long-term mechanisms. Short-term synaptic plasticity refers to changes in synaptic strength that occurs very quickly (from one-thousandth of a second to 5 minutes) and are temporary and decay over minutes (maximum 30 minutes). Long-term synaptic plasticity is defined by a long-lasting, activity-dependent change in synaptic efficacy, last from hours up to a lifetime (from 30 minutes to weeks, months, and years) and is thought to constitute the basis of learning and memory. A significant difference occurs in the nature of the change; short-term plasticity adds only a functional change, whereas long-term plasticity causes not only functional but also structural changes. Aside from genetic factors and metabolic processes, brain development is mediated also by environmental factors. Interaction with the environment plays a key role in the development and growth of neural networks and neuroplasticity. Environmental interactions that can modify and increase the development of neural networks and intelligence in children are several and are herein discussed.

Synaptic plasticity alters the strength of information flow between presynaptic and postsynaptic neurons and thus modifies the likelihood that action potentials in a presynaptic neuron will lead to an action potential in a postsynaptic neuron. As such, synaptic plasticity and pathological changes in synaptic plasticity impact the synaptic computation which controls the information flow through the neural microcircuits responsible for the complex information processing necessary to drive adaptive behaviors. As current theories of neuropsychiatric disease suggest that distinct dysfunctions in neural circuit performance may critically underlie the unique symptoms of these diseases, pathological alterations in synaptic plasticity mechanisms may be fundamental to the disease process. Here we consider mechanisms of both short-term and long-term plasticity of synaptic transmission and their possible roles in information processing by neural microcircuits in both health and disease. As paradigms of neuropsychiatric diseases with strongly implicated risk genes, we discuss the findings in schizophrenia and autism and consider the alterations in synaptic plasticity and network function observed in both human studies and genetic mouse models of these diseases. Together these studies have begun to point toward a likely dominant role of short-term synaptic plasticity alterations in schizophrenia while dysfunction in autism spectrum disorders (ASDs) may be due to a combination of both short-term and long-term synaptic plasticity alterations.

Neuromorphic computational systems that emulate biological synapses in the human brain are fundamental in the development of artificial intelligence protocols beyond the standard von Neumann architecture. Such systems require new types of building blocks, such as memristors that access a quasi-continuous and wide range of conductive states, which is still an obstacle for the realization of high-efficiency and large-capacity learning in neuromorphoric simulation. Here, we introduce hydrogen and sodium titanate nanobelts, the intermediate products of hydrothermal synthesis of TiO2 nanobelts, to emulate the synaptic behavior. Devices incorporating a single titanate nanobelt demonstrate robust and reliable synaptic functions, including excitatory postsynaptic current, paired pulse facilitation, short term plasticity, potentiation and depression, as well as learning-forgetting behavior. In particular, the gradual modulation of conductive states in the single nanobelt device can be achieved by a large number of identical pulses. The mechanism for synaptic functionality of the titanate nanobelt device is attributed to the competition between an electric field driven migration of oxygen vacancies and a thermally induced spontaneous diffusion. These results provide insight into the potential use of titanate nanobelts in synaptic applications requiring continuously addressable states coupled with high processing efficiency.

Mutations in the synaptic gene SHANK3 lead to a neurodevelopmental disorder known as Phelan-McDermid syndrome (PMS). PMS is a relatively common monogenic and highly penetrant cause of autism spectrum disorder (ASD) and intellectual disability (ID), and frequently presents with attention deficits. The underlying neurobiology of PMS is not fully known and pharmacological treatments for core symptoms do not exist. Here, we report the production and characterization of a Shank3-deficient rat model of PMS, with a genetic alteration similar to a human SHANK3 mutation. We show that Shank3-deficient rats exhibit impaired long-term social recognition memory and attention, and reduced synaptic plasticity in the hippocampal-medial prefrontal cortex pathway. These deficits were attenuated with oxytocin treatment. The effect of oxytocin on reversing non-social attention deficits is a particularly novel finding, and the results implicate an oxytocinergic contribution in this genetically defined subtype of ASD and ID, suggesting an individualized therapeutic approach for PMS.DOI: http://dx.doi.org/10.7554/eLife.18904.001

Maternal stress during pregnancy has profound effects on offspring, disrupting brain development and behaviour. Mirtazapine, an antidepressant commonly prescribed for maternal depression, has an unclear impact on offspring neurophysiology and behaviour. We hypothesized that maternal mirtazapine treatment during pregnancy and lactation would influence locomotor activity, exploratory behaviour, and hippocampal synaptic plasticity in rat offspring, particularly in the context pre-gestational stress.Offspring from control or chronically stressed dams, treated with either vehicle or mirtazapine, were assessed. Behavioural responses were evaluated using the open field test, and the hippocampus was examined electrophysiologically to measure population spike (PS) amplitude of compound action potential, field excitatory postsynaptic potential (fEPSP) slope, short-term plasticity, and long-term potentiation (LTP).Maternal stress significantly reduced exploration of the central zone, indicating increased anxiety-like behaviour, although post hoc comparisons did not reach significance. Mirtazapine treatment did not reverse these behavioural alterations. PS amplitude was unaffected across groups, but fEPSP slope was significantly reduced in stressed offspring, with no recovery observed following mirtazapine treatment. Paired-pulse ratios across inter-pulse intervals (10-100 ms) were consistently decreased in the stressed group, indicating impaired short-term synaptic plasticity, which mirtazapine did not restore. In contrast, LTP showed a significant stress×treatment interaction (p=0.0201), suggesting that mirtazapine selectively enhanced long-term plasticity in stressed offspring.Mirtazapine did not reverse behavioural impairments or basal synaptic transmission deficits induced by maternal stress. It may selectively enhance long-term synaptic plasticity, suggesting its potential to modulate specific neurodevelopmental outcomes following prenatal stress exposure.

Two-dimensional van der Waals heterostructures provide a versatile platform for multifunctional optoelectronic devices. WS2/PdSe2 heterostructures, characterized by n-type conductive behavior, exhibit persistent photoconductivity in high vacuum under negative gate voltages. This phenomenon has been leveraged to simulate synaptic functions of the human brain, including short- and long-term plasticity. Short-term plasticity was simulated, resulting in paired-pulse facilitation and post-tetanic potentiation indices of approximately 140% and 300%, respectively. By stimulating the WS2/PdSe2 heterostructure with consecutive 1 s light pulses, the learning, forgetting, and re-learning phases associated with knowledge acquisition in the human brain were replicated. Furthermore, the device was demonstrated as an optoelectronic memory, programmable with light pulses and erasable via electrical pulses on the gate electrode.

In this article, NaxCu1−xI thin-film transistors gated by chitosan for low-voltage operation have been created by doping CuI with different Na concentrations (x = 0, 0.05, 0.1). It is found that the devices exhibit optimal performance when x is 0.05: a large current on/off ratio of 1.62 × 105, a steep subthreshold slope of 17.72 mV/dec, a saturation field-effect mobility of 0.51 cm2/V s, and a threshold voltage of 1.10 V. The operating voltage of the devices is reduced to below 2 V due to the electric-double-layer (EDL) effect. At a frequency of 10 Hz, a maximum specific capacitance of 1.36 μF/cm2 can be obtained in the chitosan. The effects of bias stress and laser on Na0.05Cu0.95I thin-film transistors (TFTs) have been examined at the end of the article, and the results revealed that Na0.05Cu0.95I TFTs possess good stability. As the bias stress gets longer and the laser power increases, the transfer curves of TFTs shift positively. Also, artificial synaptic behaviors and functions have been simulated experimentally. It can be divided into single-pulse, double-pulse, and multiple-pulse. According to the experimental results, features such as short-term plasticity, long-term plasticity, paired-pulse facilitation, high-pass filtering, pulse logic, and spatial summation have been achieved. The electrostatic modulation of EDL due to proton transverse migration is vital for this simulation. The realization of low-voltage synaptic Na0.05Cu0.95I TFTs prepared by solution method with pulse logic and spatial summation functions is crucial for application of portable biosensors and neuromorphic systems.

Defect-engineering-based titanium dioxide nanowires for artificial optoelectronic synapses

Li+ electrolyte-gated transistors (EGTs) have attracted significant attention as artificial synapses because of the fast response of Li+ ion, low operating voltage, and applicability to flexible electronics. Due to the inherent nature of Li+ ion, Li+ EGTs show, however, limitations, such as poor long-term synaptic plasticity and nonlinear/nonsymmetric conductance update, which hinder the practical applications of artificial synapses. Herein, Li+ EGTs integrated with poly(vinylidene fluoride-co-trifluoroethylene) (PVDF-TrFE) ferroelectric polymer as a channel–electrolyte interlayer are presented. Owing to the polarized domains of PVDF-TrFE, the transport of Li+ ions at the channel–electrolyte interface is accelerated, and Li+ ions effectively penetrate the channel. Moreover, the self-diffusion of Li+ ions from the channel to the electrolyte is suppressed by the downward polarized domains. Li+ EGTs, therefore, successfully demonstrate synaptic characteristics, including excitatory postsynaptic current, short-/long-term synaptic plasticity, and paired-pulse facilitation. Also, conductance update in Li+ EGTs shows a dynamic range (Gmax/Gmin) of 92.42, high linearity, and distinct stability over 100 cycles. Based on their synaptic characteristics, inference simulations using a convolution neural network for the CIFAR-10 dataset imply that Li+ EGTs are suitable as artificial synapses with an inference accuracy of 89.13%. The new methodological approach addressing modulation of ion dynamics at the interface is introduced for developing practical synaptic devices.

The output of a neuronal network depends on the organization and functional properties of its component cells and synapses. While the characterization of synaptic properties has lagged cellular analyses, a potentially important aspect in rhythmically active networks is how network synapses affect, and are in turn affected by, network activity. This could lead to a potential circular interaction where short-term activity-dependent synaptic plasticity is both influenced by and influences the network output. The analysis of synaptic plasticity in the lamprey locomotor network was extended here to characterize the short-term plasticity of connections between network interneurons and to try and address its potential network role. Paired recordings from identified interneurons in quiescent networks showed synapse-specific synaptic properties and plasticity that supported the presence of two hemisegmental groups that could influence bursting: depression in an excitatory interneuron group, and facilitation in an inhibitory feedback circuit. The influence of activity-dependent synaptic plasticity on network activity was investigated experimentally by changing Ringer Ca2+ levels, and in a simple computer model. A potential caveat of the experimental analyses was that changes in Ringer Ca2+ (and compensatory adjustments in Mg2+ in some cases) could alter several other cellular and synaptic properties. Several of these properties were tested, and while there was some variability, these were not usually significantly affected by the Ringer changes. The experimental analyses suggested that depression of excitatory inputs had the strongest influence on the patterning of network activity. The simulation supported a role for this effect, and also suggested that the inhibitory facilitating group could modulate the influence of the excitatory synaptic depression. Short-term activity-dependent synaptic plasticity has not generally been considered in spinal cord models. These results provide further evidence for short-term plasticity between locomotor network interneurons. As this plasticity could influence the patterning of the network output it should be considered as a potential functional component of spinal cord networks.

The development of electronic devices possessing the functionality of biological synapses is a crucial step toward replicating the capabilities of the human brain. Of the various materials that have been used to realize artificial synapses, renewable natural materials have the advantages of being abundant, inexpensive, biodegradable, and ecologically benign. In this study, we report a biocompatible artificial synapse based on a matrix of the biopolymer ι-carrageenan (ι-car), which exploits Ag dynamics. This artificial synapse emulates the short-term plasticity (STP), paired-pulse facilitation (PPF), and transition from STP to long-term potentiation (LTP) of a biological synapse. The above-mentioned characteristics are realized by exploiting the similarities between the Ag dynamics in the ι-car matrix and the Ca2+ dynamics in a biological synapse. By demonstrating a method that uses biomaterials and Ag dynamics to emulate synaptic functions, this study confirms that ι-car has the potential for constructing neuromorphic systems that use biocompatible artificial synapses.

Just as biological synapses provide basic functions for the nervous system, artificial synaptic devices serve as the fundamental building blocks of neuromorphic networks; thus, developing novel artificial synapses is essential for neuromorphic computing. By exploiting the band alignment between 2D inorganic and organic semiconductors, the first multi-functional synaptic transistor based on a molybdenum disulfide (MoS2 )/perylene-3,4,9,10-tetracarboxylic dianhydride (PTCDA) hybrid heterojunction, with remarkable short-term plasticity (STP) and long-term plasticity (LTP), is reported. Owing to the elaborate design of the energy band structure, both robust electrical and optical modulation are achieved through carriers transfer at the interface of the heterostructure, which is still a challenging task to this day. In electrical modulation, synaptic inhibition and excitation can be achieved simultaneously in the same device by gate voltage tuning. Notably, a minimum inhibition of 3% and maximum facilitation of 500% can be obtained by increasing the electrical number, and the response to different frequency signals indicates a dynamic filtering characteristic. It exhibits flexible tunability of both STP and LTP and synaptic weight changes of up to 60, far superior to previous work in optical modulation. The fully 2D MoS2 /PTCDA hybrid heterojunction artificial synapse opens up a whole new path for the urgent need for neuromorphic computation devices.