Frequency-dependent learning achieved using semiconducting polymer/electrolyte composite cells

Mimicking efferent nerves using a graphdiyne-based artificial synapse with multiple ion diffusion dynamics

A graphdiyne-based artificial synapse (GAS), exhibiting intrinsic short-term plasticity, has been proposed to mimic biological signal transmission behavior. The impulse response of the GAS has been reduced to several millivolts with competitive femtowatt-level consumption, exceeding the biological level by orders of magnitude. Most importantly, the GAS is capable of parallelly processing signals transmitted from multiple pre-neurons and therefore realizing dynamic logic and spatiotemporal rules. It is also found that the GAS is thermally stable (at 353 K) and environmentally stable (in a relative humidity up to 35%). Our artificial efferent nerve, connecting the GAS with artificial muscles, has been demonstrated to complete the information integration of pre-neurons and the information output of motor neurons, which is advantageous for coalescing multiple sensory feedbacks and reacting to events. Our synaptic element has potential applications in bioinspired peripheral nervous systems of soft electronics, neurorobotics, and biohybrid systems of brain-computer interfaces.

GABA Regulation of Burst Firing in Hippocampal Astrocyte Neural Circuit: A Biophysical Model

It is now widely accepted that glia cells and gamma-aminobutyric acidergic (GABA) interneurons dynamically regulate synaptic transmission and neuronal activity in time and space. This paper presents a biophysical model that captures the interaction between an astrocyte cell, a GABA interneuron and pre/postsynaptic neurons. Specifically, GABA released from a GABA interneuron triggers in astrocytes the release of calcium (Ca²⁺) from the endoplasmic reticulum via the inositol 1, 4, 5-trisphosphate (IP₃) pathway. This results in gliotransmission which elevates the presynaptic transmission probability rate (PR) causing weight potentiation and a gradual increase in postsynaptic neuronal firing, that eventually stabilizes. However, by capturing the complex interactions between IP₃, generated from both GABA and the 2-arachidonyl glycerol (2-AG) pathway, and PR, this paper shows that this interaction not only gives rise to an initial weight potentiation phase but also this phase is followed by postsynaptic bursting behavior. Moreover, the model will show that there is a presynaptic frequency range over which burst firing can occur. The proposed model offers a novel cellular level mechanism that may underpin both seizure-like activity and neuronal synchrony across different brain regions.

Tunable Resistive Switching Enabled by Malleable Redox Reaction in the Nano-Vacuum Gap

Neuromorphic computing has emerged as a highly promising alternative to conventional computing. The key to constructing a large-scale neural network in hardware for neuromorphic computing is to develop artificial neurons with leaky integrate-and-fire behavior and artificial synapses with synaptic plasticity using nanodevices. So far, these two basic computing elements have been built in separate devices using different materials and technologies, which poses a significant challenge to system design and manufacturing. In this work, we designed a resistive device embedded with an innovative nano-vacuum gap between a bottom electrode and a mixed-ionic-electronic-conductor (MIEC) layer. Through redox reaction on the MIEC surface, metallic filaments dynamically grew within the nano-vacuum gap. The nano-vacuum gap provided an additional control factor for controlling the evolution dynamics of metallic filaments by tuning the electron tunneling efficiency, in analogy to a pseudo-three-terminal device, resulting in tunable switching behavior in various forms from volatile to nonvolatile switching in a single device. Our device demonstrated cross-functions, in particular, tunable neuronal firing and synaptic plasticity on demand, providing seamless integration for building large-scale artificial neural networks for neuromorphic computing.

Phase-change nanoclusters embedded in a memristor for simulating synaptic learning

A type of memristor with a structure of Pd/Nb : AlNO/Pd was designed and fabricated in this work. Its filaments are embedded by phase-change NbO nanoclusters confirmed by the analysis of cross-sectional profiles. The resistive switching mechanism includes the contribution of oxygen vacancy (VO) migration and the structural evolution of phase-change nanoclusters. The system experiences two types of kinetics under external stimulations to replicate the critical dynamics in real synapses: VO migration corresponding to the dynamics of the Ca2+ flux and transmitter release at the pre-synapse, and the phase change of the NbO nanoclusters corresponding to the ionic flux modulated by the post-synaptic potential (current). It was found that the memristor can respond to a set of pulse stimulations in a pattern containing a slow linear increase term and a periodic oscillation term, suggesting that the output signals might be encoded. The simulation of long-term plasticity indicates that the memristor is suitable for diverse learning protocols, including spike-rate dependent plasticity and spike-timing-dependent plasticity. Our work proposes an elementary cell that closely approximates biological synapses and is usable for brain-like computing.

Time-decay Memristive Behavior and diffusive dynamics in one forget process operated by a 3D vertical Pt/Ta2O5-x/W device

A time-decay resistive switching memory using a 3D vertical Pt/Ta2O5-x/W device architecture is demonstrated, in which horizontal W electrodes were fabricated, and vertical Pt electrodes was formed at the sidewall after oxide was deposited. Unlike conventional resistive switching, which usually form a conductive filament connect two electrodes, a weak conductive filament was formed from bottom electrode W to near top electrode Pt. The memory can be recovered with a time scale when the electrical stimulation is removed. However, different decay behaviors were observed in one decay curve, including rapid decay and slow decay processes. This can be a good simulation of different stages of forgetting. By a combination of the current decay fitting and the conductive analysis, the rapid decay and slow decay processes correspond to ion diffusion and electron detrapping, respectively.

Diverse Synaptic Plasticity Induced by the Interplay of Ionic Polarization and Doping at Salt-Doped Electrolyte/Semiconducting Polymer Interface

Pt/Ca²⁺-polyethylene oxide/polymer poly[3-hexylthiophene-2,5-diyl]/Pt devices were fabricated, and their pulse responses were studied. The discharging peak, represented by the postsynaptic current (PSC), first increases and then decreases with increasing input number in a pulse train. The weight of the PSC decreased for low-frequency stimulations but increased for high-frequency stimulations. However, the peak of the negative differential resistance during the charging process varied following the opposite trend. These behaviors suggested the ability for transferring the signal bidirectionally, confirming the equivalence between the ionic kinetics of our device and the transmitter kinetics of one kind of synapse. A facilitation (F)-depression (D) interplay model corresponding to the ionic polarization and doping interplay at the electrolyte/semiconducting polymer interface was adopted to successfully mimic the weight modification of the PSC. The simulation results showed that the observed synaptic plasticity was caused by the great disparity between the recovery time constants of F and D (τ _F and τ _D ). Moreover, such an interplay could inspire the features of responses to post-tetanic stimulations. Our study suggested a means to realize synaptic computation.

Spatial summation of the short-term plasticity of a pair of organic heterogeneous junctions

Short-term plasticity of a pair of organic heterogeneous junctions could be linearly summed from those of the two sources.

Simulation of synaptic short-term plasticity using Ba(CF3SO3)2-doped polyethylene oxide electrolyte film

The simulation of synaptic plasticity using new materials is critical in the study of brain-inspired computing. Devices composed of Ba(CF3SO3)2-doped polyethylene oxide (PEO) electrolyte film were fabricated and with pulse responses found to resemble the synaptic short-term plasticity (STP) of both short-term depression (STD) and short-term facilitation (STF) synapses. The values of the charge and discharge peaks of the pulse responses did not vary with input number when the pulse frequency was sufficiently low(~1 Hz). However, when the frequency was increased, the charge and discharge peaks decreased and increased, respectively, in gradual trends and approached stable values with respect to the input number. These stable values varied with the input frequency, which resulted in the depressed and potentiated weight modifications of the charge and discharge peaks, respectively. These electrical properties simulated the high and low band-pass filtering effects of STD and STF, respectively. The simulations were consistent with biological results and the corresponding biological parameters were successfully extracted. The study verified the feasibility of using organic electrolytes to mimic STP.

Effect of heavy-ion on frequency selectivity of semiconducting polymer/electrolyte heterojunction

Long-term bidirectional frequency selectivity has been achieved in MEH-PPV/PEO–Nd³⁺cells, which suggests spike-rate-dependent plasticity learning protocol. It depends on pulse shape due to variation of ionic type.