Paired-pulse Depression Research Articles

Self-Powered Dye-Sensitized Solar-Cell-Based Synaptic Devices for Multi-Scale Time-Series Data Processing in Physical Reservoir Computing.

Physical reservoir computing (PRC) using synaptic devices has attracted attention as a promising edge artificial intelligence device. To handle time-series data on various time scales, it is necessary to fabricate devices with the desired time scale. In this study, we fabricated a dye-sensitized solar-cell-based synaptic device with controllable time constants by changing the light intensity. This device showed synaptic features, such as paired-pulse facilitation and paired-pulse depression, in response to light intensity. Moreover, we found that the high computational performance of the time-series data processing task was achieved by changing the light intensity, even when the input pulse width was varied. In addition, the fabricated device can be used for motion recognition tasks. This study paves the way for realizing multiple time-scale PRC.

ZnO-based artificial synaptic diodes with zero-read voltage for neural network computing

Brain-inspired neuromorphic sensory devices play a crucial role in addressing the limitations of von Neumann systems in contemporary computing. Currently, synaptic devices rely on memristors and thin-film transistors, requiring the establishment of a read voltage. A built-in electric field exists within the p–n junction, enabling the operation of zero-read-voltage synaptic devices. In this study, we propose an artificial synapse utilizing a ZnO diode. Typical rectification curves characterize the formation of ZnO diodes. ZnO diodes demonstrate distinct synaptic properties, including paired-pulse facilitation, paired-pulse depression, long-term potentiation, and long-term depression modulations, with a read voltage of 0 V. An artificial neural network is constructed to simulate recognition tasks using MNIST and Fashion-MNIST databases, achieving test accuracy values of 92.36% and 76.71%, respectively. This research will pave the way for advancing zero-read-voltage artificial synaptic diodes for neural network computing.

Chronic ethanol exposure in mice evokes pre- and postsynaptic deficits in GABAergic transmission in ventral tegmental area GABA neurons.

GABAergic neurons in mouse ventral tegmental area (VTA) exhibit elevated activity during withdrawal following chronic ethanol exposure. While increased glutamatergic input and decreased GABAA receptor sensitivity have been implicated, the impact of inhibitory signaling in VTA GABA neurons has not been fully addressed. We used electrophysiological and ultrastructural approaches to assess the impact of chronic intermittent ethanol vapour exposure in mice on GABAergic transmission in VTA GABA neurons during withdrawal. We used CRISPR/Cas9 ablation to mimic a somatodendritic adaptation involving the GABAB receptor (GABABR) in ethanol-naïve mice to investigate its impact on anxiety-related behaviour. The frequency of spontaneous inhibitory postsynaptic currents was reduced in VTA GABA neurons following chronic ethanol treatment and this was reversed by GABABR inhibition, suggesting chronic ethanol strengthens the GABABR-dependent suppression of GABAergic input to VTA GABA neurons. Similarly, paired-pulse depression of GABAA receptor-dependent responses evoked by optogenetic stimulation of nucleus accumbens inputs from ethanol-treated mice was reversed by GABABR inhibition. Somatodendritic currents evoked in VTA GABA neurons by GABABR activation were reduced following ethanol exposure, attributable to the suppression of GIRK (Kir3) channel activity. Mimicking this adaptation enhanced anxiety-related behaviour in ethanol-naïve mice. Chronic ethanol weakens the GABAergic regulation of VTA GABA neurons in mice via pre- and postsynaptic mechanisms, likely contributing to their elevated activity during withdrawal and expression of anxiety-related behaviour. As anxiety can promote relapse during abstinence, interventions targeting VTA GABA neuron excitability could represent new therapeutic strategies for treatment of alcohol use disorder.

Modulating Neuromorphic Behavior of Organic Synaptic Electrolyte-Gated Transistors Through Microstructure Engineering and Potential Applications.

Organic synaptic transistors are a promising technology for advanced electronic devices with simultaneous computing and memory functions and for the application of artificial neural networks. In this study, the neuromorphic electrical characteristics of organic synaptic electrolyte-gated transistors are correlated with the microstructural and interfacial properties of the active layers. This is accomplished by utilizing a semiconducting/insulating polyblend-based pseudobilayer with embedded source and drain electrodes, referred to as PB-ESD architecture. Three variations of poly(3-hexylthiophene) (P3HT)/poly(methyl methacrylate) (PMMA) PB-ESD-based organic synaptic transistors are fabricated, each exhibiting distinct microstructures and electrical characteristics, thus serving excellent samples for exploring the critical factors influencing neuro-electrical properties. Poor microstructures of P3HT within the active layer and a flat active layer/ion-gel interface correspond to typical neuromorphic behaviors such as potentiated excitatory postsynaptic current (EPSC), paired-pulse facilitation (PPF), and short-term potentiation (STP). Conversely, superior microstructures of P3HT and a rough active layer/ion-gel interface correspond to significantly higher channel conductance and enhanced EPSC and PPF characteristics as well as long-term potentiation behavior. Such devices were further applied to the simulation of neural networks, which produced a good recognition accuracy. However, excessive PMMA penetration into the P3HT conducting channel leads to features of a depressed EPSC and paired-pulse depression, which are uncommon in organic synaptic transistors. The inclusion of a second gate electrode enables the as-prepared organic synaptic transistors to function as two-input synaptic logic gates, performing various logical operations and effectively mimicking neural modulation functions. Microstructure and interface engineering is an effective method to modulate the neuromorphic behavior of organic synaptic transistors and advance the development of bionic artificial neural networks.

Self-rectifying NiOX/WOX heterojunction synaptic memristor for crossbar architectured reservoir computing system

In this study, we examine an ITO/NiOX/WOX/Pt p-n heterojunction memristor for neuromorphic applications as a synaptic crossbar array. The transition in the depletion region at the interface between p-type NiOX and n-type WOX crucially influences the self-rectifying characteristics of the device depending on the voltage polarity. Furthermore, long- and short-term memory coexist depending on the switching voltage condition, thus enabling various neuromorphic applications, such as reservoir computing and the use of the synaptic device at the off-chip trained network. The reliable operational characteristics are confirmed by obtaining an average memory window (>9) and rectification ratio (>58) between device-to-device and cycle-to-cycle. Furthermore, synaptic functions were successfully implemented, such as spike-rate-dependent plasticity, spike-number-dependent plasticity, paired-pulse facilitation, post-tetanic potentiation, paired-pulse depression, and post-tetanic depression, in conjunction with repeatability. Ultimately, reservoir computing is accomplished based on the I–V nonlinearity and short-term memory characteristics. A high pattern recognition rate (>96.2 %) is achieved in MNIST tasks using 16 reservoir states, thus affirming the trustworthiness of the reservoir computing system. With its comprehensive approach to synaptic applications for neuromorphic computing systems, the heterojunction device highlights its considerable potential to advance artificial neural networks in conjunction with novel memristor technology directions.

Spike-enhanced synapse functions of SnOx-based resistive memory

This paper explores the application of resistive random-access memory (RRAM) devices in emulating various synapse functions. The electrical properties of an indium tin oxide (ITO)/SnOx/TaN device are examined, including the activation process, switching process, endurance (>102), and retention characteristics (104 s). A conduction mechanism for the resistive-switching process based on the migration of oxygen ions in the insulating SnOx film is proposed. Furthermore, the multilevel cell characteristics of the device, demonstrating the control of resistance states by variations in reset voltage and compliance current, were found to be suitable, increasing its data storage capacity. Synapse functions, including potentiation and depression, are tested, and their repeatability is evaluated. A neural network-based Modified National Institute Standards and Technology pattern recognition system is applied to the ITO/SnOx/TaN device, showcasing its capabilities in pattern recognition tasks. This study further explores various synapse functions, such as paired-pulse facilitation, paired-pulse depression, excitatory postsynaptic current, and activity-dependent synaptic plasticity. Hebbian learning rules, including spike rate-dependent plasticity, are demonstrated, along with spike time-dependent plasticity under various spike types, making it suitable for high-functionality neuromorphic applications. Finally, we assembled 3 × 3 synapse arrays and utilized them to form recognizable patterns, demonstrating the potential of the device in implementing neural network functions.

Design of gelatin-based bionic device for neural computing applications

This study introduces an approach to the development of resistive random-access memory (RRAM) devices by utilizing gelatin-based materials and incorporating an ultrathin Al2O3 interface layer fabricated using atomic layer deposition (ALD). The integration of the ALD technology for Al2O3 deposition ensures precise control over the layer thickness and quality, contributing to enhanced device uniformity and stability. The AGAI device can withstand more than 200 switching cycles while maintaining a high ON/OFF ratio exceeding 103, and it also successfully emulates synaptic plasticity characteristics, including long-term synaptic plasticity and short-term synaptic plasticity, as demonstrated by their responses to paired-pulse facilitation and paired-pulse depression, respectively, thereby validating their potential for neural computing applications. Additionally, the hybrid conduction mechanism in the AGAI device, involving aluminum and oxygen vacancy filaments, provides remarkable control over the switching process, leading to repeatability in synaptic characteristics and resistance states. These capabilities introduce new possibilities for the development of neuromorphic computing systems, which aim to mimic the functionality of the human brain in processing and storing information.

Prefrontal cortical network dysfunction from acute neurotoxicant exposure.

Prefrontal cortical (PFC) dysfunction has been linked to disorders exhibiting deficits in cognitive performance, attention, motivation, and impulse control. Neurons of the PFC are susceptible to glutamatergic excitotoxicity, an effect associated with cortical degeneration in frontotemporal disorders (FTDs). PFC susceptibility to environmental toxicant exposure, one possible contributor to sporadic FTD, has not been systematically studied. Here, we tested the ability of a well-known environmental neurotoxicant, methylmercury (MeHg), to induce hyperexcitability in medial prefrontal cortex (mPFC) excitatory pyramidal neurons, using whole cell patch-clamp recording. Acute MeHg exposure (20 μM) produced significant mPFC dysfunction, with a shift in the excitatory to inhibitory (E-I) balance toward increased excitability. Both excitatory postsynaptic current (EPSC) and inhibitory postsynaptic current (IPSC) charges were significantly increased after MeHg exposure. MeHg increased EPSC frequency, but there was no observable effect on IPSC frequency, EPSC amplitude or IPSC amplitude. Neither evoked AMPA receptor- nor NMDA receptor-mediated EPSC amplitudes were affected by MeHg. However, excitatory synapses experienced a significant reduction in paired-pulse depression and probability of release. In addition, MeHg induced temporal synchrony in spontaneous IPSCs, reflecting mPFC inhibitory network dysfunction. MeHg exposure also produced increased intrinsic excitability in mPFC neurons, with an increase in action potential firing rate. The observed effects of MeHg on mPFC reflect key potential mechanisms for neuropsychological symptoms from MeHg poisoning. Therefore, MeHg has a significant effect on mPFC circuits known to contribute to cognitive and emotional function and might contribute to etiology of neurodegenerative diseases, such as FTD.NEW & NOTEWORTHY Prefrontal cortical neurons are highly susceptible to glutamatergic excitotoxicity associated with neuronal degeneration in frontal dementia and to environmental toxicant exposure, one potential contributor to FTD. However, this has not been systematically studied. Our results demonstrate that methylmercury exposure leads to hyperexcitability of prefrontal cortical neurons by shifting excitatory to inhibitory (E-I) balance and raising sensitivity for spiking. Our results provide a mechanism by which environmental neurotoxicants may contribute to pathogenesis of diseases such as FTD.

Lateral ionic-gated graphene synaptic transistor with transition from paired-pulse facilitation to depression for filtering and image recognition

The transition from paired-pulse facilitation to paired-pulse depression is of significant importance for regulating biologic neural network. Here, we fabricate and investigate a lateral ionic-gated graphene synaptic transistor (GST) with short gate length. We control the channel current via e-field-dependent movement and diffusion of ions for realizing the transition from paired-pulse facilitation to depression. This phenomenon comes from the over-diffusion and trapping of a finite number of ions and the short ion-diffusion length under large negative gate pulse stimuli. This device successfully emulates facilitation and depression synaptic functions, for leveraging the accumulation, migration and diffusion of ions. Moreover, enhanced high-pass filtering and conversion from long-term depression to long-term potentiation are achieved by changing pulses time interval. Our results indicate that our device possesses excellent frequency-dependent synaptic plasticity, making it highly suitable for information filtering up to 33 Hz in neuromorphic systems, and image edge enhancement for neural image processing. In additional, a simulated artificial neural network built on lateral ionic-gated GSTs for handwritten digit recognition can achieve a learning accuracy of 82.4 %.

Enhanced Release Probability without Changes in Synaptic Delay during Analogue-Digital Facilitation.

Neuronal timing with millisecond precision is critical for many brain functions such as sensory perception, learning and memory formation. At the level of the chemical synapse, the synaptic delay is determined by the presynaptic release probability (Pr) and the waveform of the presynaptic action potential (AP). For instance, paired-pulse facilitation or presynaptic long-term potentiation are associated with reductions in the synaptic delay, whereas paired-pulse depression or presynaptic long-term depression are associated with an increased synaptic delay. Parallelly, the AP broadening that results from the inactivation of voltage gated potassium (Kv) channels responsible for the repolarization phase of the AP delays the synaptic response, and the inactivation of sodium (Nav) channels by voltage reduces the synaptic latency. However, whether synaptic delay is modulated during depolarization-induced analogue-digital facilitation (d-ADF), a form of context-dependent synaptic facilitation induced by prolonged depolarization of the presynaptic neuron and mediated by the voltage-inactivation of presynaptic Kv1 channels, remains unclear. We show here that despite Pr being elevated during d-ADF at pyramidal L5-L5 cell synapses, the synaptic delay is surprisingly unchanged. This finding suggests that both Pr- and AP-dependent changes in synaptic delay compensate for each other during d-ADF. We conclude that, in contrast to other short- or long-term modulations of presynaptic release, synaptic timing is not affected during d-ADF because of the opposite interaction of Pr- and AP-dependent modulations of synaptic delay.

Memory device based on MoS2-polyvinyl alcohol for simulating synaptic behavior

A memory device based on MoS2-polyvinyl alcohol was fabricated. As a good dispersant, polyvinyl alcohol solution can disperse 2D layered materials more evenly in the solution. The 19 states of the device conductance are modulated step by step by direct current scanning, which makes it possible to perform the computing task in memory. Then, the presence of conductive filaments allows the resistance state of the memristor to be dynamically transformed, which is similar to some basic behavior of biological synapses. Further, a variety of conductivity states such as short-term potentiation, short term depression, long term potentiation and long-term depression behavior are modulated by applying voltage to simulate the basic behavior of biological synapses. Finally, the paired pulse facilitation, paired pulse depression, spiking timing dependent plasticity and spiking voltage dependent plasticity behaviors of biological synapses are simulated in memristor devices.

Optimizing assessment of low frequency H-reflex depression in persons with spinal cord injury.

Considering the growing interest in clinical applications of neuromodulation, assessing effects of various modulatory approaches is increasingly important. Monosynaptic spinal reflexes undergo depression following repeated activation, offering a means to quantify neuromodulatory influences. Following spinal cord injury (SCI), changes in reflex modulation are associated with spasticity and impaired motor control. To assess disrupted reflex modulation, low-frequency depression (LFD) of Hoffman (H)-reflex excitability is examined, wherein the amplitudes of conditioned reflexes are compared to an unconditioned control reflex. Alternatively, some studies utilize paired-pulse depression (PPD) in place of the extended LFD train. While both protocols induce similar amounts of H-reflex depression in neurologically intact individuals, this may not be the case for persons with neuropathology. We compared the H-reflex depression elicited by PPD and by trains of 3-10 pulses to an 11-pulse LFD protocol in persons with incomplete SCI. The amount of depression produced by PPD was less than an 11-pulse train (mean difference = 0.137). When compared to the 11-pulse train, the 5-pulse train had a Pearson's correlation coefficient (R) of 0.905 and a coefficient of determination (R2) of 0.818. Therefore, a 5-pulse train for assessing LFD elicits modulation similar to the 11-pulse train and thus we recommend its use in lieu of longer trains.

Self‐assembled vapor-transport-deposited SnS nanoflake-based memory devices with synaptic learning properties

The most salient features of resistive switching (RS) devices are low energy consumption, fast switching speed, and high-density integration, which render them promising candidates for realizing non-volatile memory and artificial synaptic devices. However, the growth of functional switching layers for RS devices needs innovative deposition techniques. Herein, we utilize a high-throughput vapor-transport-deposition (VTD) technique for synthesizing self-assembled tin-sulfide (SnS) nanoflakes, which are then used as a switching layer to fabricate an RS device. First principle calculations are conducted to understand the optoelectronic properties of SnS by employing density functional theory. The proposed Ag/SnS/Pt memory device exhibits substantial merits, including low-switching voltages (VSET: 0.22 V and VRESET: −0.20 V), suitable ON/OFF ratio (∼259), excellent endurance (106), and extended memory retention (106 s) characteristics. In addition, RS stochasticity is modeled using statistical time-series analysis via Holt’s exponential smoothing. Interestingly, the device can emulate multiple synaptic functionalities, including potentiation, depression, paired-pulse facilitation, paired-pulse depression, excitatory postsynaptic current, inhibitory postsynaptic current, and advanced spike-timing dependent plasticity rules. Moreover, the proposed synaptic device can detect the edge of images by utilizing a convolutional neural network. The unique and efficient VTD-SnS-based device will be a potential candidate for high-density non-volatile memory and neuromorphic computing applications.

Neuromorphic sensing of biomolecules covalently immobilised on polydimethyl glutarimide

Polydimethyl glutarimide (PMGI) layers with sub-micron thicknesses have been modified in a 2.5 kV Ar plasma immersion ion implantation (PIII) process to introduce free radical covalent binding sites. The surface roughness of the PMGI increased after the PIII treatment but no through-layer defects were observed. When applied to the treated PMGI, horseradish peroxidase (HRP) enzyme remained bound to the surface after extended immersion in sodium dodecyl sulfate solution (SDS). Hence, covalent binding between the activated surface and enzyme was confirmed. This covalent binding was achieved up to 24-h after the PIII process. The treated PMGI was then incorporated as a gate dielectric layer within a lateral three-terminal electrolyte-gated device. The device output characteristics resembled those of post-synaptic outputs; as successive (pre-synaptic) voltage pulses were applied to the gate, paired pulse depression and spike rate dependent plasticity were observed in the source-drain (post-synaptic) current. These characteristics were altered by the presence of HRP immobilised on the plasma-modified PMGI gate dielectric layer thus providing readout detection. These results and preliminary device characteristics show the potential for the plasma functionalized PMGI as a sensitive and reproducible biosensing technology.

Coexistence of synaptic behaviour and negative differential resistance at room temperature in the resistive switching device based on natural indigo molecules

The memory storage and processing capability of human brain is throwing excitement and challenges to create a low power consuming “brain-like functioning device” called neuromorphic device which is the basis of automation and robotics. We demonstrate a robust and highly efficient two-terminal device (Al/Indigo/Al) based on natural indigo molecules to emulate synaptic functionalities for use in neuromorphic applications. The indigo molecules are sourced from plants and are stable at room temperature. Molecules exhibit an optical energy gap of ∼ 1.9 eV evidenced by UV–vis spectroscopy. A detailed analysis of conduction mechanism is performed via dc-electrical characteristics. Consistent negative differential resistance (NDR) is observed, which we attribute to the deep trap states. The analysis shows that conduction is due to the trap-assisted Poole-Frenkel effec. The device maintains an extremely stable high-resistance state (HRS) and low resistance state (LRS) up to 9000 cycles of read – write - erase operation. Further, the essential characteristics such as paired pulse facilitation (PPF) and paired pulse depression (PPD) have been measured on the device. Potentiation (learning) and depression (forgetting) curves follow double exponential with more than 85% of the potentiation/depression occurring in the initial few pulses. Non-linearity (NL) calculations suggest that the device performance can be tuned by carefully choosing the pulse voltage and pulse width such that the nonlinearity factor is reduced. This work clearly indicates an easy approach for the fabrication of natural organic molecule-based artificial synapse that works efficiently at room temperature, as well as the method for selecting measurement parameters to obtain low-power consuming artificial synapse.

3D-Printed Intrinsically Stretchable Organic Electrochemical Synaptic Transistor Array.

Organic electrochemical transistors (OECTs) for skin-like bioelectronics require mechanical stretchability, softness, and cost-effective large-scale manufacturing. However, developing intrinsically stretchable OECTs using a simple and fast-response technique is challenging due to limitations in functional materials, substrate wettability, and integrated processing of multiple materials. In this regard, we propose a fabrication method devised by combining the preparation of a microstructured hydrophilic substrate, multi-material printing of functional inks with varying viscosities, and optimization of the device channel geometries. The resulting intrinsically stretchable OECT array with synaptic properties was successfully manufactured. These devices demonstrated high transconductance (22.5 mS), excellent mechanical softness (Young's modulus ∼ 2.2 MPa), and stretchability (∼30%). Notably, the device also exhibited artificial synapse functionality, mimicking the biological synapse with features such as paired-pulse depression, short-term plasticity, and long-term plasticity. This study showcases a promising strategy for fabricating intrinsically stretchable OECTs and provides valuable insights for the development of brain-computer interfaces.

Enhanced synaptic weight in ferroelectric PbZr0.52Ti0.48O3 thin film by inserting semiconductor Sr2IrO4 layer

Ferroelectric memristors based on metal/ferroelectric/semiconductor structure are suitable for the simulation of non-volatile synaptic weight due to the high on/off switching ratio, low energy consumption, high precision and fast working speed. Especially, the characteristics of the semiconductor electrode are closely related to the synaptic performance of the device. Here, ferroelectric memristors (PbZr0.52Ti0.48O3/Nb:SrTiO3 and PbZr0.52Ti0.48O3/Sr2IrO4) with different semiconductor electrodes were fabricated by introducing Sr2IrO4 (SIO) thin film. Various plasticity have been successfully simulated under different electrical impulses, such as inhibitory postsynaptic current (IPSC), paired pulse depression (PPD), spike rate dependent plasticity (SRDP) and spike time dependent plasticity (STDP) in the two devices. Moreover, the absolute values of synaptic weight and the relaxation time of PbZr0.52Ti0.48O3 (PZT)/SIO have been significantly improved. This may be attributed to the fact that the small work function of SIO increases the variation of the interface barrier at the device. And the artificial synaptic device based on PZT/SIO is used to achieve the application of Morse code. This study plays an important role in achieving efficient storage and computation for neuromorphic computing.

Enhanced synaptic performances in SrIrO3 thin films by a ferroelectric layer

SrIrO3 (SIO) with a perovskite structure exhibits broad application prospects in electronic synapses due to its high carrier mobility, scalability, and compatibility with silicon technology. On the other hand, ferroelectric polarization can efficiently and directionally regulate the movement of carriers, which provides the possibility to improve the synaptic properties of such materials. In this study, electronic synapses based on the SIO epitaxial film with introducing a ferroelectric PbZr0.2Ti0.8O3 (PZT) layer, multiple important synaptic plasticity functions including paired-pulse depression, spike-rate-dependent plasticity, spike-time-dependent plasticity, and abnormal Bienenstock–Cooper–Munro learning rule have been simulated by electrical stimulation. Furthermore, the PZT/SIO/Nb:SrTiO3 (NSTO) device exhibits larger synaptic weight and dynamic range of conductance and requires less training pulses compared to the SIO/NSTO device, which may be attributed to the enhanced modulation of the variation in the SIO/NSTO interface barrier by the polarization field. This research makes a great contribution to the efficient and fast information transmission of neuromorphic computing.

Nano-crystalline ZnO memristor for neuromorphic computing: Resistive switching and conductance modulation

In this work, a nano-crystalline (NC) ZnO-based memristor was fabricated to investigate the short-term memory characteristics for reservoir computing systems. The crystalline structure of the ZnO film was confirmed through transmission electron microscopy (TEM) and X-ray diffraction pattern (XRD), while X-ray photoelectron spectroscopy (XPS) confirmed the chemical and bonding states of each element. The NC-ZnO-based memristor exhibited remarkable endurance, enduring more than 200 DC cycles, and had a high to low resistance (RH/RL) ratio of 102. Furthermore, it displayed long data retention of 104 s and consistent resistive switching (RS) with restricted variation in the set and reset voltage, showing its excellent performance characteristics. By controlling the pulse amplitude and the time interval between pulses, it was possible to effectively replicate the key features of short-term synaptic plasticity, including potentiation, depression, and paired-pulse depression, through conductance modulation. An artificial neural network (ANN) simulation achieved a pattern recognition accuracy of approximately 90.1% for a 28 × 28-pixel image after 100 training epochs. Based on this extensive study, NC-ZnO-based memristor exhibits immense potential as a crucial element in constructing high-performance neuromorphic computing systems.

Latent toxoplasmosis impairs learning and memory yet strengthens short-term and long-term hippocampal synaptic plasticity at perforant pathway-dentate gyrus, and Schaffer collatterals-CA1 synapses

Investigating long-term potentiation (LTP) in disease models provides essential mechanistic insight into synaptic dysfunction and relevant behavioral changes in many neuropsychiatric and neurological diseases. Toxoplasma (T) gondii is an intracellular parasite causing bizarre changes in host’s mind including losing inherent fear of life-threatening situations. We examined hippocampal-dependent behavior as well as in vivo short- and long-term synaptic plasticity (STP and LTP) in rats with latent toxoplasmosis. Rats were infected by T. gondii cysts. Existence of REP-529 genomic sequence of the parasite in the brain was detected by RT-qPCR. Four and eight weeks after infection, spatial, and inhibitory memories of rats were assessed by Morris water maze and shuttle box tests, respectively. Eight weeks after infection, STP was assessed in dentate gyrus (DG) and CA1 by double pulse stimulation of perforant pathway and Shaffer collaterals, respectively. High frequency stimulation (HFS) was applied to induce LTP in entorhinal cortex-DG (400 Hz), and CA3-CA1 (200 Hz) synapses. T. gondii infection retarded spatial learning and memory performance at eight weeks post-infection period, whereas inhibitory memory was not changed. Unlike uninfected rats that normally showed paired-pulse depression, the infected rats developed paired-pulse facilitation, indicating an inhibitory synaptic network disruption. T. gondii-infected rats displayed strengthened LTP of both CA1-pyramidal and DG-granule cell population spikes. These data indicate that T. gondii disrupts inhibition/excitation balance and causes bizarre changes to the post-synaptic neuronal excitability, which may ultimately contribute to the abnormal behavior of the infected host.