Long-term Plasticity Research Articles

Environmentally Stable and Reconfigurable Ultralow-Power Two-Dimensional Tellurene Synaptic Transistor for Neuromorphic Edge Computing.

While neuromorphic computing can define a new era for next-generation computing architecture, the introduction of an efficient synaptic transistor for neuromorphic edge computing still remains a challenge. Here, we envision an atomically thin 2D Te synaptic device capable of achieving a desirable neuromorphic edge computing design. The hydrothermally grown 2D Te nanosheet synaptic transistor apparently mimicked the biological synaptic nature, exhibiting 100 effective multilevel states, a low power consumption of ∼110 fJ, excellent linearity, and short-/long-term plasticity. Furthermore, the 2D Te synaptic device achieved reconfigurable MNIST recognition accuracy characteristics of 88.2%, even after harmful detergent environment infection. We believe that this work serves as a guide for developing futuristic neuromorphic edge computing.

A ferroelectric memristor with a capacitor-like structure for neuromorphic computing

This paper presents a ferroelectric memristor-based synaptic device with a capacitor-like structure and nonvolatile multilevel conductance. Conductance modulation can be achieved by manipulating the barrier height through polarization inversion and the mimicking of the important synaptic functions, such as long-term plasticity and spike-timing-dependent plasticity, have been implemented. By extracting device parameters, a simulated artificial neural network is constructed for image recognition, and it can achieve 91.2% recognition accuracy for Modified National Institute of Standards and Technology images. These results show the potential of this device in building brain-like computing systems and further enrich the research of ferroelectric materials in realizing artificial synapses.

A Reconfigurable Optoelectronic Synaptic Transistor with Stable Zr‐CsPbI3 Nanocrystals for Visuomorphic Computing (Adv. Mater. 12/2023)

Synaptic Transistors In article 2208497, Haifeng Ling, Linghai Xie, Wei Huang, and co-workers propose a wavelength-aware reconfigurable synaptic transistor for visuomorphic computing. Based on the broadband absorption of Zr-CsPbI3 perovskite nanocrystals, reconfigurability between short-term plasticity and long-term plasticity for the device is realized. A vision sensor array is constructed to simulate image pre-processing and recognition with a homogeneous architecture.

Molecular Structure Engineering of Polyelectrolyte Bilayer-Based Memristors: Implications for Linear Potentiation and Depression Characteristics

Critical to artificial intelligence’s future is emulating biological synapses with memristors. Moreover, according to a wide variety, low cost, simple fabrication, and good flexibility, organic materials provide a competitive approach in memristor and synapse emulation, especially in devices where ions carry current. Polyelectrolytes with different molecular structures were used as functional layers in this study to enhance the memory and synapse performance of polyelectrolyte bilayer-based memristors, performed by ions, and polyelectrolyte chain migration caused a potential drop change at the interface of the ∼15 nm thick polyelectrolyte bilayer and its electrodes. Consequently, the memory device with strong polyelectrolyte sodium poly(styrene sulfonic acid) (PSS) and poly(diallyl dimethylammonium chloride) (PDAC), which were prepared by spin-coating, shows outstanding resistive switching performance and synapse functionalities than those with weak polyelectrolytes and/or polyelectrolytes without a ring structure. Particularly, the indium tin oxide (ITO)/PSS/PDAC/ITO device shows almost linear potentiation and depression characteristics by applying continuous pulse voltage, which results in high performance on the artificial neural network simulation as 90% on the Mixed National Institute of Standards and Technology data set. The steric hindrance between the two polyelectrolytes with the five-ring structure can be attributed to the causation of linear conductance update. Furthermore, it shows short- and long-term plasticity during potentiation and depression, which is essential for the development of neuromorphic systems with complex cognitive capabilities.

Amyloid–Gold Nanoparticle Hybrids for Biocompatible Memristive Devices

Biomolecular materials offer tremendous potential for the development of memristive devices due to their low cost of production, environmental friendliness, and, most notably, biocompatibility. Herein, biocompatible memristive devices based on amyloid-gold nanoparticle hybrids have been investigated. These memristors demonstrate excellent electrical performance, featuring an ultrahigh Roff/Ron ratio (>107), a low switching voltage (<0.8 V), and reliable reproducibility. Additionally, the reversible transition from threshold switching to resistive switching mode was achieved in this work. The arrangement of peptides in amyloid fibrils endows the surface polarity and phenylalanine packing, which provides channels for the migration of Ag ions in the memristors. By modulating voltage pulse signals, the study successfully imitates the synaptic behavior of excitatory postsynaptic current (EPSC), paired-pulse facilitation (PPF), and the transition from short-term plasticity (STP) to long-term plasticity (LTP). More interestingly, Boolean logic standard cells were designed and simulated using the memristive devices. The fundamental and experimental results of this study thus offer insights into the utilization of biomolecular materials for advanced memristive devices.

Organic Memristor with Synaptic Plasticity for Neuromorphic Computing Applications

Memristors have been considered to be more efficient than traditional Complementary Metal Oxide Semiconductor (CMOS) devices in implementing artificial synapses, which are fundamental yet very critical components of neurons as well as neural networks. Compared with inorganic counterparts, organic memristors have many advantages, including low-cost, easy manufacture, high mechanical flexibility, and biocompatibility, making them applicable in more scenarios. Here, we present an organic memristor based on an ethyl viologen diperchlorate [EV(ClO4)]2/triphenylamine-containing polymer (BTPA-F) redox system. The device with bilayer structure organic materials as the resistive switching layer (RSL) exhibits memristive behaviors and excellent long-term synaptic plasticity. Additionally, the device's conductance states can be precisely modulated by consecutively applying voltage pulses between the top and bottom electrodes. A three-layer perception neural network with in situ computing enabled was then constructed utilizing the proposed memristor and trained on the basis of the device's synaptic plasticity characteristics and conductance modulation rules. Recognition accuracies of 97.3% and 90% were achieved, respectively, for the raw and 20% noisy handwritten digits images from the Modified National Institute of Standards and Technology (MNIST) dataset, demonstrating the feasibility and applicability of implementing neuromorphic computing applications utilizing the proposed organic memristor.

Effects of altered-reality training on interocular disinhibition in amblyopia.

Training of viewing an altered-reality environment dichoptically has been found to reactivate human adult ocular dominance plasticity, allowing improvement of vision for amblyopia. One suspected mechanism for this training effect is ocular dominance rebalancing through interocular disinhibition. Here, we investigated whether the training modulated the neural responses reflecting interocular inhibition. Thirteen patients with amblyopia and 11 healthy controls participated in this study. Before and after six daily altered-reality training sessions, participants watched flickering video stimuli with their steady-state visually evoked potential (SSVEP) signals recorded simultaneously. We assessed the amplitude of SSVEP response at intermodulation frequencies, which was a potential neural indicator of interocular suppression. The results showed that training weakened the intermodulation response only in the amblyopic group, which was in agreement with the hypothesis that the training reduced interocular suppression specific to amblyopia. Moreover, even one month after the training ended, we could still observe this neural training effect. These findings provide preliminary neural evidence in support of the disinhibition account for treating amblyopia. We also explain these results with the ocular opponency model, which, to our knowledge, is the first time for this binocular rivalry model to be used in explaining long-term ocular dominance plasticity.

Improvement of polarization switching in ferroelectric transistor by interface trap reduction for brain-inspired artificial synapses

Numerous devices have been studied to accomplish a brain-inspired neuromorphic computing system; however, their characteristics require improvement to enhance operation accuracy of neuromorphic systems. Here, we propose a ferroelectric field-effect transistor based on Hf0.5Zr0.5O2 for a high-performance artificial synaptic device by reducing interface trap density. Using polarization in the Hf0.5Zr0.5O2 ferroelectric layer, threshold voltage is precisely controlled to achieve synaptic characteristics. However, synaptic characteristics are degraded because interface traps cause threshold voltage shift in the direction opposite to the threshold voltage shift by polarization. Therefore, oxygen plasma treatment was performed to minimize degradation by interface traps. Thus, outstanding synaptic characteristics including the linearity of the weight update, the max/min weight ratio, and the number of weights were observed. Furthermore, high repeatability and long-term plasticity was observed at low operating power. Therefore, our study demonstrated a promising method for implementing a high-accuracy, low-power neuromorphic system with progressed artificial synaptic devices.

AReconfigurable Optoelectronic Synaptic Transistor with Stable Zr-CsPbI3 Nanocrystals for Visuomorphic Computing.

Reconfigurable phototransistor memory attracts considerable attention for adaptive visuomorphic computing, with highlyefficient sensing, memory, and processing functions integrated onto a single device. However, developing reconfigurable phototransistor memory remains a challenge due to the lack of anall-optically controlled transition between short-term plasticity (STP) and long-term plasticity (LTP). Herein, an air-stable Zr-CsPbI3 perovskite nanocrystal (PNC)-based phototransistor memory is designed,whichis capable of broadband photoresponses. Benefitting from the different electron capture ability of Zr-CsPbI3 PNCs to 650 and 405nm light, anartificial synapse and non-volatile memory can be created on-demand and quickly reconfigured within a single device for specific purposes. Owing to the optically reconfigurable and wavelength-aware operation between STP and LTP modes, the integrated blue feature extraction and target recognition can be demonstrated in a homogeneous neuromorphic vision sensor array. This work suggests a new way in developing perovskite optoelectronic transistors for highly efficient in-sensor computing.

An artificial bridge circuit approach between two biological neurons using nanoscale topologies towards paralytic disorders

The advent of Nanoscale IC technology towards pulse-based neural systems reactivates the dead nervous about restoring the functionality of paralytic disorders. This work reports in first time a design of a novel CMOS biological neuron system, which replaces a dead neuron between two neurons to restore communication in paralyzed individuals. The work binds into three stages: design of a spiking leaky Integrator and Fire (LIF) neuron with refractory period mechanisms, which achieves a low power consumption of 2.4 μW, in the first stage; an adaptive homeostatic synapse with short and long-term spike plasticity, that reconfigure the spiking neuron networks of multichannel sensor electrodes to record the electric signal from the active cell as second stage; the final stage presents a low-power common source current reuse regulated cascode (CS-CR-RGC) TIA for amplifying the weak synapse current signal, which achieves a high gain of 135.71 dBΩ with an optimized noise performance of 0.19 pA/Hz. The entire work is designed and implemented using a CMOS 65 nm commercial process that occupies a die area of 400 μm × 120 μm.

All-Optically Controlled Artificial Synapses Based on Light-Induced Adsorption and Desorption for Neuromorphic Vision.

Artificial synapses with the capability of optical sensing and synaptic functions are fundamental components to construct neuromorphic visual systems. However, most reported artificial optical synapses require a combination of optical and electrical stimuli to achieve bidirectional synaptic conductance modulation, leading to an increase in the processing time and system complexity. Here, an all-optically controlled artificial synapse based on the graphene/titanium dioxide (TiO2) quantum dot heterostructure is reported, whose conductance could be reversibly tuned by the effects of light-induced oxygen adsorption and desorption. Synaptic behaviors, such as excitatory and inhibitory, short-term and long-term plasticity, and learning-forgetting processes, are implemented using the device. An artificial neural network simulator based on the artificial synapse was used to train and recognize handwritten digits with a recognition rate of 92.2%. Furthermore, a 5 × 5 optical synaptic array that could simultaneously sense and memorize light stimuli was fabricated, mimicking the sensing and memory functionality of the retina. Such an all-optically controlled artificial synapse shows a promising prospect in the application of perception, learning, and memory tasks for future neuromorphic visual systems.

Optoelectronic Memristive Synapse Behavior for the Architecture of Cu2ZnSnS4@BiOBr Embedded in Poly(methyl methacrylate).

The great potential of artificial optoelectronic devices that are capable of mimicking biosynapse functions in brain-like neuromorphic computing applications has aroused extensive interest, and the architecture design is decisive yet challenging. Herein, a new architecture of p-type Cu2ZnSnS4@BiOBr nanosheets embedded in poly(methyl methacrylate) (PMMA) films (CZTS@BOB-PMMA) is presented acting as a switching layer, which not only shows the bipolar resistive switching features (SET/RESET voltages, ∼ -0.93/+1.35 V; retention, >104 s) and electrical- and near-infrared light-induced synapse plasticity but also demonstrates electrical-driven excitatory postsynaptic current, spiking-time-dependent plasticity, paired pulse facilitation, long-term plasticity, long- and short-term memory, and "learning-forgetting-learning" behaviors. The approach is a rewarding attempt to broaden the research of optoelectric controllable memristive devices for building neuromorphic architectures mimicking human brain functionalities.

Ferroelectrically modulated ion dynamics in Li+ electrolyte-gated transistors for neuromorphic computing

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.

Role of the NMDAR-GluN2B subunits in the function of supramolecular NMDAR-BK channel complexes.

Large conductance calcium- and voltage-activated potassium channels (BK) are widely expressed across many tissues, contributing to many physiological functions. Membrane depolarization and relatively high (micromolar) intracellular concentrations of Ca2+ are required for their activation. Such concentrations are reached in the vicinity of Ca2+-permeant ion channels, to which BK proteins are closely located in various tissues, including the brain. N-methyl-D-aspartate receptors (NMDAR) are sodium (Na+)- and Ca2+-conducting glutamate-activated ion channels that are functionally coupled to BK channels in the olfactory bulb and the dentate gyrus, contributing to decreased neuronal intrinsic excitability. Recently, our group demonstrated that postsynaptic NMDAR-BK complexes at basal dendrites of somatosensory cortex layer 5 pyramidal neurons regulate synaptic transmission and long-term plasticity. However, the specific contribution of different NMDAR subunits (GluN1 and GluN2A/GluN2B) to the NMDAR-BK interaction remains elusive. Defects in this association may be of pathological relevance in the context of EIEE27 syndrome (epileptic encephalopathy, early infantile, 27), which has been related to mutations in the GluN2B-encoding gene (GRIN2B). In this work I aimed to understand the role of GluN2B subunits in the function of NMDAR-BK complexes and, more specifically, if GluN2B-related human mutations modify NMDAR-BK coupling. Function of NMDAR-BK complexes containing different EIEE27-related GluN2B mutations was examined using electrophysiology in heterologous expression systems. Proximity between channel proteins within complexes was assessed using in situ proximity ligation assay (PLA). Membrane expression efficiency was studied employing TIRF microscopy (Total Internal Reflection Fluorescence). Our results reveal some disease-related GluN2B mutations reduce the NMDAR-BK interaction, either by altered interactions with BK channels and/or by functional uncoupling between the channels within the NMDAR-BK complexes.

Evidence for long-term potentiation in lipid membranes.

Biological supramolecular assemblies, such as phospholipid bilayer membranes, have been used to demonstrate signal processing via short-term synaptic plasticity (STP) in the form of paired pulse facilitation (PPF) and depression (PPD), thus showing that model membranes have the potential to emulate the brain's efficiency and flexible cognitive capabilities. However, STP memory states in lipid bilayers are volatile and cannot be stored or accessed over relevant periods of time, a central requirement for learning. Using droplet interface bilayers (DIBs) composed of lipids and hexadecane, we apply an electrical stimulation protocol featuring repetitive voltage cycling in the form of a sinusoidal waveform. We show that DIBs displaying memcapacitance can also exhibit long-term synaptic plasticity in the form of long-term potentiation (LTP) associated with capacitive energy storage in the phospholipid bilayer. The time scales for the physical changes associated with LTP range between minutes to hours and are substantially longer than previous STP studies, where stored energy dissipated after only a few seconds. While STP behavior is the result of changes in bilayer geometry associated with reversible changes in bilayer area and thickness, LTP is the result of molecular and structural changes due to the zwitterionic lipid headgroups and the dielectric properties of the lipid bilayer that result from the buildup of an increasingly asymmetric charge distribution between the bilayer interfaces.

Presenilins regulate synaptic plasticity in the perforant pathways of the hippocampus

Mutations in the Presenilin genes (PSEN1 and PSEN2) are the major cause of familial Alzheimer’s disease (AD), highlighting the importance of Presenilin (PS) in AD pathogenesis. Previous studies of PS function in the hippocampus demonstrated that loss of PS results in the impairment of short- and long-term synaptic plasticity and neurotransmitter release at hippocampal Schaffer collateral (SC) and mossy fiber (MF) synapses. Cortical input to the hippocampus through the lateral perforant pathway (LPP) and the medial perforant pathway (MPP) is critical for normal cognitive functions and is particularly vulnerable during aging and early stages of AD. Whether PS regulates synaptic function in the perforant pathways, however, remained unknown. In the current study, we investigate PS function in the LPP and MPP by performing whole-cell and field-potential electrophysiological recordings using acute hippocampal slices from postnatal forebrain-restricted excitatory neuron-specific PS conditional double knockout (cDKO) mice. We found that paired-pulse ratio (PPR) is reduced in the LPP and MPP of PS cDKO mice. Moreover, synaptic frequency facilitation or depression in the LPP or MPP, respectively, is impaired in PS cDKO mice. Notably, depletion of intracellular Ca2+ stores by inhibition of sarcoendoplasmic reticulum Ca2+ ATPase (SERCA) minics and occludes the effects of PS inactivation, as evidenced by decreases of the evoked excitatory postsynaptic currents (EPSCs) amplitude in the LPP and MPP of control neurons but no effect on the EPSC amplitude in PS cDKO neurons, suggesting that impaired intracellular calcium homeostasis in the absence of PS may contribute to the observed deficits in synaptic transmission. While spontaneous synaptic events, such as both the frequency and the amplitude of spontaneous or miniature EPSCs, are similar between PS cDKO and control neurons, long-term potentiation (LTP) is impaired in the LPP and MPP of PS cDKO mice, accompanied with reduction of evoked NMDA receptor-mediated responses. These findings show the importance of PS in the regulation of synaptic plasticity and intracellular calcium homeostasis in the hippocampal perforant pathways.

CPEB3 low-complexity motif regulates local protein synthesis via protein–protein interactions in neuronal ribonucleoprotein granules

Biomolecular condensates, membraneless organelles found throughout the cell, play critical roles in many aspects of cellular function. Ribonucleoprotein granules (RNPs) are a type of biomolecular condensate necessary for local protein synthesis and are involved in synaptic plasticity and long-term memory. Most of the proteins in RNPs possess low-complexity motifs (LCM), allowing for increased promiscuity of protein-protein interactions. Here, we describe the importance of protein-protein interactions mediated by the LCM of RNA-binding protein cytoplasmic polyadenylation element binding protein 3 (CPEB3). CPEB3 is necessary for long-term synaptic plasticity and memory persistence, but the mechanisms involved are still not completely elucidated. We now present key mechanisms involved in its regulation of synaptic plasticity. We find that CPEB3-LCM plays a role in appropriate local protein synthesis of messenger ribonucleic acid (mRNA) targets, through crucial protein-protein interactions that drive localization to neuronal Decapping protein 1 (DCP1)-bodies. Translation-promoting CPEB3 and translation-inhibiting CPEB1 are packaged into neuronal RNP granules immediately after chemical long-term potentiation is induced, but only translation-promoting CPEB3 is repackaged to these organelles at later time points. This localization to neuronal RNP granules is critical for functional influence on translation as well as overall local protein synthesis (measured as α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid (AMPA) insertion into the membrane and localization to the synapse). We therefore conclude that protein-protein interaction between the LCM of CPEB3 plays a critical role in local protein synthesis by utilizing neuronal RNP granules.

Voltage modulated long-term plasticity in perovskite heterostructured memristive synaptic devices with high-performance neuromorphic computing

The development of neuromorphic computing is expected to enable the computer to realize the integration of storage and computation. The development of memristors provides hardware support possibilities for the development of neuromorphic computing. In this work, we have prepared a (La0.67, Sr0.33)MnO3/BaTiO3-based memristor with good forward and reverse memristor function and multilevel resistive tunability, including an increased resistance state at forward voltage and a decreased resistance state at reverse voltage. This is mainly due to the barriers of the ferroelectric dielectric layer and its ferroelectric polarization under the electric field, and the migration of oxygen vacancy under the electric field. The devices also successfully implement the synaptic simulations of short-term plasticity, long-term plasticity, excitatory postsynaptic current, paired-pulse facilitation, spike-rate-dependent plasticity, and spike-timing-dependent plasticity and reimplement these synaptic simulations by varying the amplitude and pulse width of the applied voltage. We have also achieved a classification accuracy of 96.7% for the given handwritten digit data by an artificial neural network with supervised learning. The high classification accuracy is attributed to the good nonlinearity of the device in terms of continuous conductance decreased (0.91) and increased (0.58). Our results are expected to provide a good reference value for neural devices.

Efficient UV-Sensitive Si-In-ZnO-Based Photo-TFT and Its Behavior as an Optically Stimulated Artificial Synapse

Integration of optoelectronic synaptic devices as neuromorphic vision sensors has currently attracted significant attention due to their ability of imitating human visual systems. Low-power-consuming UV-sensitive phototransistors fabricated using amorphous oxide semiconductors are one of the potential contenders for the development of optically stimulated synaptic devices. Herein, amorphous Si-In-ZnO (a-SIZO)-based UV-sensitive photo thin-film transistors (photo-TFTs) were fabricated, which exhibited an efficient spectral photoresponsivity of 4.93 × 103 A/W and detectivity of 5.47 × 1015 jones at 350 nm wavelength. Considerable photoresponse in the visible range (450–650 nm) was also observed. The presence of persistent photoconductivity (PPC) in the photoresponse characteristics enabled the photo-TFT to perform simultaneously as an optically stimulated artificial synapse. The typical synaptic behaviors such as excitatory post-synaptic current (EPSC), pair-pulse facilitation (PPF), short-term plasticity (STP) to long-term plasticity (LTP), etc. were demonstrated efficiently by the fabricated photo-TFT, indicating its learning and memorizing capabilities similar to a biological synapse. The concurrent demonstration of efficient UV range photoresponse and optically stimulated synaptic behavior enables the a-SIZO-based photo-TFT as a promising pathway toward the development of artificial visual sensors which can be integrated into future neuromorphic systems.

A decrease in NR2B expression mediated by DNA hypermethylation induces perioperative neurocognitive disorder in aged mice.

This study was designed to investigate the role of NR2B and the contribution of DNA methylation to NR2B expression in the pathogenesis of PND. Eighteen-month-old C57BL/6J mice were subjected to experimental laparotomy under 1.4% isoflurane anesthesia. Hippocampus-dependent learning and memory were evaluated by using the Barnes maze and contextual fear conditioning tests. The protein and mRNA expression levels of NR2B were evaluated by western blotting and qRT-PCR respectively, and the methylation of the NR2B gene was examined by using targeted bisulfite sequencing. Long-term synaptic plasticity (LTP) was measured by electrophysiology. Mice that underwent laparotomy exhibited hippocampus-dependent cognitive deficits accompanied by decreased NR2B expressions and LTP deficiency. The overexpression of NR2B in the dorsal hippocampus could improve learning and memory in mice subjected to laparotomy. In particular, the decreased NR2B expressions induced by laparotomy was attributed to the NR2B gene hypermethylation. Preoperative administration of S-adenosylmethionine (SAM) could hypomethylate the NR2B gene, upregulate NR2B expression and improve LTP, exerting a dose-dependent therapeutic effect against PND. Moreover, inhibiting NR2B abrogated the benefits of SAM pretreatment. Laparotomy cause hippocampus-dependent cognitive decline by hypermethylating the NR2B gene, allowing us to understand the pathogenesis of PND in an epigenetic landscape.