Channel Conductance Research Articles

Side-Gated Iontronic Memtransistor: A Fast and Energy-Efficient Neuromorphic Building Block.

Iontronic memtransistors have emerged as technologically superior to conventional memristors for neuromorphic applications due to their low operating voltage, additional gate control, and enhanced energy efficiency. In this study, a side-gated iontronic organic memtransistor (SG-IOMT) device is explored as a potential energy-efficient hardware building block for fast neuromorphic computing. Its operational flexibility, which encompasses the complex integration of redox activities, ion dynamics, and polaron generation, makes this device intriguing for simultaneous information storage and processing, as it effectively overcomes the von Neumann bottleneck of conventional computing. The SG-IOMT device achieves linear channel conductance performance metrics with switching speeds in the microsecond range and energy efficiency down to a few femtojoules, comparable to those of the brain. This finding demonstrates robustness, supporting the Atkinson-Shiffrin memorization model, and the four most common Hebbian learning rules. Overall, this SG-IOMT device architecture offers significant advantages over conventional architectures, as it yields remarkable image classification performance in convolutional neural network simulations.

A Cascaded Duplex Organic Vertical Memory with Learning Rate Scheduling for Efficient Artificial Neural Network Training

AbstractLearning rate scheduling (LRS) is a critical factor influencing the performance of neural networks by accelerating the convergence of learning algorithms and enhancing the generalization capabilities. The escalating computational demands in artificial intelligence (AI) necessitate advanced hardware solutions capable of supporting neural network training with LRS. This not only requires linear and symmetric analog programming capabilities but also the precise adjustment of channel conductance to achieve tunable slope in weight update behaviors. Here, a cascaded duplex organic vertical memory is proposed with the coupling of ferroelectric polarization effect and Schottky gate control on the same semiconducting channel, exhibiting adjustable‐slope conductance update with high linearity and symmetry. Therefore, in the chest X‐ray image detection, a fast‐to‐slow LRS is used for a bi‐layer ANN training, achieving a rapid, stable convergence behavior within only 15 epochs and a high recognition accuracy. Moreover, the proposed LRS training is also suitable for the Mackey Glass prediction task using long short‐term memory networks. This work integrates LRS into synaptic devices, enabling efficient hardware implementation of neural networks and thus enhancing AI performance in practical applications.

NMR and molecular simulation studies on the structure elucidation of the amphotericin B ion channel using 13C and 19F labelling.

Amphotericin B (AmB) has been clinically used for serious fungal infections for over 60 years. The drug is characterized by its specific recognition of ergosterol (Erg) in the fungal cell membrane. AmB and Erg form an ion-channel assembly, which is thought to play a major role in the antibiotic activity of AmB. The precise structure of the ion channel in fungal membranes still remains unelucidated. Recently, the structure of an AmB assembly formed in artificial lipid bilayers was determined using solid-state NMR and molecular dynamics simulations. The structure elucidation was made possible by using 13C- and 19F-labelled AmBs, which were efficiently synthesized using strategies and methods established in previous studies. This review focuses on the structure of the AmB ion channel, which accounts for the antibiotic activity. Additionally, the chemical syntheses of isotope-labelled AmB and Erg used for the structural studies are also reviewed. Solid-state NMR spectra of the labelled AmBs were recorded to measure the distances between labelled sites in the AmB-Erg assembly in lipid bilayers, revealing that the ion channel consisting of seven molecules of AmB spans the bilayer with a single molecule length. Extensive molecular dynamics simulations showed that the conductance of this AmB channel is comparable with those by single-channel recording. The simulations also demonstrated that Erg stabilizes the ion-channel assemblies more efficiently than human cholesterol. The atomic-level structure of the AmB channel in the artificial bilayer will help us to understand the mechanisms of the pharmacological actions and adverse effects of AmB.

A compact 4T1M2C AMOLED pixel circuit with multimodal drive transistor

We propose a 5-transistor, 2-capacitor (5T2C) AMOLED pixel circuit using a multimodal transistor (MMT) as driver, which may be more appropriately referred to as 4T1M2C to reflect the inclusion of a device which is distinctly different from conventional Ohmic-contact thin-film transistors (TFTs). The MMT is a type of contact-controlled transistor, here implemented with a Schottky source. Its gating mechanisms separate ‘analog' charge injection, controlled by the source contact, from ‘digital' channel conductance switching. The mixed-signal operation of the MMT allows it to perform the function of multiple conventional transistors in a power- and area-efficient manner, enabling pixel circuit design to achieve superior image uniformity and energy efficiency, due to the combination of threshold compensation scheme and inherent saturation properties of the MMT drive transistor.

Estradiol elicits distinct firing patterns in arcuate nucleus kisspeptin neurons of females through altering ion channel conductances

Estradiol elicits distinct firing patterns in arcuate nucleus kisspeptin neurons of females through altering ion channel conductances

Estradiol elicits distinct firing patterns in arcuate nucleus kisspeptin neurons of females through altering ion channel conductances.

Hypothalamic kisspeptin (Kiss1) neurons are vital for pubertal development and reproduction. Arcuate nucleus Kiss1 (Kiss1ARH) neurons are responsible for the pulsatile release of gonadotropin-releasing hormone (GnRH). In females, the behavior of Kiss1ARH neurons, expressing Kiss1, neurokinin B (NKB), and dynorphin (Dyn), varies throughout the ovarian cycle. Studies indicate that 17β-estradiol (E2) reduces peptide expression but increases Slc17a6 (Vglut2) mRNA and glutamate neurotransmission in these neurons, suggesting a shift from peptidergic to glutamatergic signaling. To investigate this shift, we combined transcriptomics, electrophysiology, and mathematical modeling. Our results demonstrate that E2 treatment upregulates the mRNA expression of voltage-activated calcium channels, elevating the whole-cell calcium current that contributes to high-frequency burst firing. Additionally, E2 treatment decreased the mRNA levels of canonical transient receptor potential (TPRC) 5 and G protein-coupled K+ (GIRK) channels. When Trpc5 channels in Kiss1ARH neurons were deleted using CRISPR/SaCas9, the slow excitatory postsynaptic potential was eliminated. Our data enabled us to formulate a biophysically realistic mathematical model of Kiss1ARH neurons, suggesting that E2 modifies ionic conductances in these neurons, enabling the transition from high-frequency synchronous firing through NKB-driven activation of TRPC5 channels to a short bursting mode facilitating glutamate release. In a low E2 milieu, synchronous firing of Kiss1ARH neurons drives pulsatile release of GnRH, while the transition to burst firing with high, preovulatory levels of E2 would facilitate the GnRH surge through its glutamatergic synaptic connection to preoptic Kiss1 neurons.

Ion permeation through a narrow cavity constriction in KCNQ1 channels: Mechanism and implications for pathogenic variants

KCNQ1 potassium channels play a pivotal role in the physiology and pathophysiology of several human excitable and epithelial tissues. The latest cryo-electron microscopy (cryo-EM) structures provide unique insights into channel function and pharmacology, opening avenues for different therapeutic strategies against human diseases associated with KCNQ1 mutations. However, these structures also raise fundamental questions about the mechanisms of ion permeation. Cryo-EM structures thought to represent the open state of the channel feature a cavity region not wide enough for accommodation of hydrated K+. To understand how K+ passes through the cavity constriction, we utilized microsecond-scale molecular dynamics (MD) simulations using the KCNQ1/KCNE3 cryo-EM structure, characterized mutants at the G345 residue situated at the narrowest point of the cavity, and recorded single channels. The findings indicate that ions become partially dehydrated at the constriction, which enables permeation. MD simulations demonstrate that the constriction can impede the flow of ions through the channel's pore, a finding that is corroborated by mutational screening and single-channel recordings. Reduced channel conductance is the key mechanism underlying reported pathological KCNQ1 mutations at or near the constriction site.

Nanofibrous carbon (multi-wall carbon nanotubes): synthesis and electrochemical studies by using field-effect transistor setup

Synthesis of nanofibrous carbon (multi-wall carbon nanotubes, MWCNTs) by means of n-hexane pyrolysis is reported. The structure of the obtained MWCNTs was studied using scanning electron microscopy, and the diameters of 20–85 nm and lengths of 500–600 nm for these nanotubes were observed. By using the above mentioned MWCNTs field-effect transistors were fabricated on ITO glass substrates with a gate dielectric made of 390 nm thick Al2O3 foil and the drain-source contacts made of 300 nm thick aluminum foil. The Nano-C film 200 nm thick was deposited by thermal evaporation in vacuum. The properties of the obtained field-effect transistors were studied. The current-voltage characteristics of the OFET show an increase in currents with a positive voltage on the gate, which corresponds to the electron conductivity of the transport channel. The dependences are nonlinear, and there are no saturation regions in the output characteristics. The Raman spectra indicate the presence of nickel and show characteristic peaks for C=C and CH bonds.

Plasma etching of silicon carbide trenches with high aspect ratio and rounded corners

Silicon carbide (SiC) is a representative third-generation semiconductor known for its superior properties, including a wide band gap, high electron saturation velocity, high thermal conductivity, and high physical/chemical stability, making it highly promising for high-power electronic devices. In SiC power devices, superjunction architecture can reduce specific on-resistance without compromising breakdown voltage, while trench-gate structures provide better control over channel conductivity. In this work, we demonstrate high aspect ratio (>5:1) SiC trenches for superjunction devices and corner-rounded SiC trenches for gate trench power devices through plasma etching. The high aspect ratio trenches were achieved by optimizing the gas ratio in the etching process, and the corner-rounded trenches were directly formed by introducing nitrogen dilution during plasma etching. These results are significant for enhancing the performance of SiC trench-based power devices.

Study of AC Conductivity and Relaxation Times Depending on Moisture Content in Nanocomposites of Insulation Pressboard-Innovative Bio-Oil-Water Nanodroplets.

The aim of this study was to determine the frequency-temperature dependence of the AC conductivity and relaxation times in humid electrical pressboard used in the insulation of power transformers, impregnated with the innovative NYTRO® BIO 300X bio-oil produced from plant raw materials. Tests were carried out for a composite of cellulose-bio-oil-water nanodroplets with a moisture content of 0.6% by weight to 5% by weight in the frequency range from 10-4 Hz to 5·103 Hz. The measurement temperatures ranged from 20 °C to 70 °C. The current conductivity in percolation channels in cellulose-bio insulating oil-water nanodroplets nanocomposites was analyzed. In such nanocomposites, DC conduction takes place via electron tunneling between the potential wells formed by the water nanodroplets. It was found that the value of the percolation channel resistance is lowest in the case of a regular arrangement of the nanodroplets. As disorder increases, characterized by an increase in the standard deviation value, the percolation channel resistance increases. It was found that the experimental values of the activation energy of the conductivity and the relaxation time of the composite of cellulose-bio-oil-water nanodroplets are the same within the limits of uncertainty and do not depend on the moisture content. The value of the generalized activation energy is ΔE ≈ (1.026 ± 0.0160) eV and is constant over the frequency and temperature ranges investigated. This study shows that in the lowest frequency region, the conductivity value does not depend on frequency. As the frequency increases further, the relaxation time decreases; so, the effect of moisture on the conductivity value decreases. The dependence of the DC conductivity on the moisture content was determined. For low moisture contents, the DC conductivity is practically constant. With a further increase in water content, there is a sharp increase in DC conductivity. Such curves are characteristic of the dependence of the DC conductivity of composites and nanocomposites on the content of the conducting phase. A percolation threshold value of xc ≈ (1.4 ± 0.3)% by weight was determined from the intersection of flat and steeply sloping sections. The frequency dependence of the values of the relative relaxation times was determined for composites with moisture contents from 0.6% by weight to 5% by weight for a measurement temperature of 60 °C. The highest relative values of the relaxation time τref occur for direct current and for the lowest frequencies close to 10-4 Hz. As the frequency increases further, the relaxation time decreases. The derivatives d(logτref)/d(logf) were calculated, from the analysis of which it was determined that there are three stages of relaxation time decrease in the nanocomposites studied. The first occurs in the frequency region from 10-4 Hz to about 3·10-1 Hz, and the second from about 3·10-1 Hz to about 1.5·101 Hz. The beginning of the third stage is at a frequency of about 1.5·101 Hz. The end of this stage is above the upper range of the Frequency Domain Spectroscopy (FDS) meter, which is 5·103 Hz. It has been established that the nanodroplets are in the cellulose and not in the bio-oil. The occurrence of three stages on the frequency dependence of the relaxation time can be explained when the fibrous structure of the cellulose is taken into account. Nanodroplets, found in micelles, microfibrils and in the fibers of which cellulose is composed, can have varying distances between nanodroplets, determined by the dimensions of these cellulose components.

(Invited) Ferroelectric Thin-Film Transistors for Memory and Neuromorphic Device Applications

Ferroelectric materials boast a remarkable ability to maintain polarization states independently of external electric fields. This unique trait makes them ideal candidates for manipulating polarization through applied electric fields, effectively influencing the domains within these materials. By modulating polarization states, we gain precise control over channel conductance, rendering ferroelectric materials highly suitable for integration as gate dielectric layers in transistors. The incorporation of ferroelectric layers into transistors enables the regulation of channel conductance, empowering precise control over a device's electrical properties. Consequently, this enhances their effectiveness as memory elements. This innovative approach not only drives the development of high-density memory devices but also bestows ferroelectric transistors with analog memory characteristics. This quality significantly broadens their potential applications, particularly in neuromorphic devices striving to emulate the complexities of biological neural networks. In summary, ferroelectric transistors represent a promising frontier in memory technology, offering not only high-density memory solutions but also the potential to revolutionize the field of neuromorphic computing. This presentation explores these compelling prospects, detailing strategies to fully exploit the capabilities of ferroelectric materials in memory and computational applications.

Nanometer-thick TiO2 channel thin film transistors as radical monitors for plasma enhanced atomic layer deposition

Nanometer-thick-TiO2-channel thin-film transistors (TFTs) are examined as oxidizing-agent monitors for room-temperature atomic layer deposition (RTALD). RTALD is a plasma-based process using plasma-excited humidified argon where OH radicals oxidize the precursor-gas adsorbed surface. In the TFT, the anatase TiO2 channel, with a thickness of 16 nm, is attached to a 300 nm thick gate capacitor of SiO2, while the channel surface is exposed to the ALD ambient. A heavily doped n-type Si substrate attached to the gate SiO2 is used as the gate electrode. The gate width and length are 1000 and 60 μm, respectively. When the TFT is installed in the RTALD chamber, the drain-current waveform is recorded in the course of the metal organic gas adsorption, evacuation of the residual gas, oxidization, and evacuation. In the present study, three kinds of metal organic (MO) precursors, tetrakis(dimethyl)amino titanium, tris(dimethyl)amino silane, and trimethyl aluminum are examined. The drain current exhibits strong responses upon the exposure of the plasma excited humidified argon. This suggests that OH radicals in the plasma might oxidize the adsorbed MO precursors to produce the OH moieties, where the surface polarization of OH moieties might enhance channel conductivity. The experimental results suggest the applicability of the present TFT as a plasma monitor in RTALD.

Ultrafast reconfigurable direct charge trapping devices based on few-layer MoS2

Abstract Charge trapping devices incorporating 2D materials and high-κ dielectrics have emerged as promising candidates for compact, multifunctional memory devices compatible with silicon-based manufacturing processes. However, traditional charge trapping devices encounter bottlenecks including complex device structure and low operation speed. Here, we demonstrate an ultrafast reconfigurable direct charge trapping device utilizing only a 30 nm-thick Al2O3 trapping layer with a MoS2 channel, where charge traps reside within the Al2O3 bulk confirmed by transfer curves with different gate-voltage sweeping rates and photoluminescence (PL) spectra. The direct charging tapping device shows exceptional memory performance in both three-terminal and two-terminal operation modes characterized by ultrafast three-terminal operation speed (∼300 ns), an extremely low OFF current of 10−14 A, a high ON/OFF current ratio of up to 107, and stable retention and endurance properties. Furthermore, the device with a simple symmetrical structure exhibits V D polarity-dependent reverse rectification behavior in the high resistance state (HRS), with a rectification ratio of 105. Additionally, utilizing the synergistic modulation of the conductance of the MoS2 channel by V D and V G, it achieves gate-tunable reverse rectifier and ternary logic capabilities.

BDNF Differentially Affects Low- and High-Frequency Neurons in a Primary Nucleus of the Chicken Auditory Brainstem.

Neurotrophins are proteins that mediate neuronal development using spatiotemporal signaling gradients. The chicken nucleus magnocellularis (NM), an analogous structure to the mammalian anteroventral cochlear nucleus, provides a model system in which signaling between the brain-derived neurotrophic factor (BDNF) and tyrosine receptor kinase B (TrkB) is temporally regulated. In the NM, TrkB expression is high early in development (embryonic [E] day 9) and is downregulated until maturity (E18-21). It is currently unknown how BDNF-TrkB signaling affects neuronal properties throughout development and across a spatial (i.e., frequency) axis. To investigate this, we exogenously applied BDNF onto NM neurons ex vivo and studied intrinsic properties using whole-cell patch clamp electrophysiology. Early in development (E13), when TrkB expression is detectable with immunohistochemistry, BDNF application slowed the firing of high-frequency NM neurons, resembling an immature phenotype. Current measurements and biophysical modeling revealed that this was mediated by a decreased conductance of the voltage-dependent potassium channels. Interestingly, this effect was seen only in high-frequency neurons and not in low-frequency neurons. BDNF-TrkB signaling induced minimal changes in late-developing NM neurons (E20-21) of high and low frequencies. Our results indicate that normal developmental downregulation of BDNF-TrkB signaling promotes neuronal maturation tonotopically in the auditory brainstem, encouraging the appropriate development of neuronal properties.

Analysis of the effect of permeant solutes on the hydraulic resistance of the plasma membrane in cells of Chara corallina.

In the cells of Chara corallina, permeant monohydric alcohols including methanol, ethanol and 1-propanol increased the hydraulic resistance of the membrane (Lpm-1). We found that the relative value of the hydraulic resistance (rLpm-1) was linearly dependent on the concentration (Cs) of the alcohol. The relationship is expressed in the equation: rLpm-1 = ρmCs + 1, where ρm is the hydraulic resistance modifier coefficient of the membrane. Ye et al. (2004) showed that membrane-permeant glycol ethers also increased Lp-1. We used their data to estimate Lpm-1 and rLpm-1. The values of rLpm-1 fit the above relation we found for alcohols. When we plotted the ρm values of all the permeant alcohols and glycol ethers against their molecular weights (MW), we obtained a linear curve with a slope of 0.014M-1/MW and with a correlation coefficient of 0.99. We analyzed the influence of the permeant solutes on the relative hydraulic resistance of the membrane (rLpm-1) as a function of the external (π0) and internal (πi) osmotic pressures. The analysis showed that the hydraulic resistance modifier coefficients (ρm) were linearly related to the MW of the permeant solutes with a slope of 0.012M-1/MW and with a correlation coefficient of 0.84. The linear relationship between the effects of permeating solutes on the hydraulic resistance modifier coefficient (ρm) and the MW can be explained in terms of the effect of the effective osmotic pressure on the hydraulic conductivity of water channels. The result of the analysis suggests that the osmotic pressure and not the size of the permeant solute as proposed by (Ye et al., J Exp Bot 55:449-461, 2004) is the decisive factor in a solute's influence on hydraulic conductivity. Thus, characean water channels (aquaporins) respond to permeant solutes with essentially the same mechanism as to impermeant solutes.

Network of artificial olfactory receptors for spatiotemporal monitoring of toxic gas.

Excessive human exposure to toxic gases can lead to chronic lung and cardiovascular diseases. Thus, precise in situ monitoring of toxic gases in the atmosphere is crucial. Here, we present an artificial olfactory system for spatiotemporal recognition of NO2 gas flow by integrating a network of chemical receptors with a near-sensor computing. The artificial olfactory receptor features nano-islands of metal-based catalysts that cover the graphene surface on the heterostructure of an AlGaN/GaN two-dimensional electron gas (2DEG) channel. Catalytically dissociated NO2 molecules bind to graphene, thereby modulating the conductivity of the 2DEG channel. For the energy/resource-efficient gas flow monitoring, trust-region Bayesian optimization algorithm allocates many sensors optimally in a complex space. Integrated artificial neural networks on a compact microprocessor with a network of sensors provide in situ gas flow predictions. This system enhances protective measures against toxic environments through spatiotemporal monitoring of toxic gases.

Electromagnetic Model of K‐Changes

AbstractK‐changes are observed as step‐like increases in the thundercloud electric fields. The K‐changes occur in the late part of intra‐cloud lightning or during negative cloud‐to‐ground lightning between return strokes. It has been shown that the processes leading to K‐changes initiate in the decayed part of a positive leader channel and propagate toward the flash origin. They are often accompanied by microsecond‐scale electric field pulses. We introduce a new model to simulate processes leading to the K‐changes in cloud‐to‐ground lightning. Our method is based on the full solution of Maxwell's equations coupled to Poisson's equation for the thundercloud charge structure. To model the K‐changes, we gradually increase the decayed channel conductivity. The modeled current wavefront propagates due to the K‐processes downward along a vertical channel and completely attenuates before reaching the ground. We derive the evolution of the linear charge densities and the scalar electric potential along the channel leading to K‐changes. We model electrostatic step‐like changes in the measured electric field together with the approximate rates and amplitudes of the microsecond scale pulses. Step‐like changes increase their amplitudes with the length of the simulated channel and with a higher conductivity of the channel. The microsecond‐scale pulse waveshapes depend mainly on the propagation velocity of the current wave, and the time scale of the conductivity increase. We show that our modeled waveforms are in a good agreement with observations conducted in Florida.

Neuropeptide-dependent spike time precision and plasticity in circadian output neurons.

Circadian rhythms influence various physiological and behavioral processes such as sleep-wake cycles, hormone secretion, and metabolism. Circadian output neurons are a group of neurons that receive input from the central circadian clock located in the suprachiasmatic nucleus of the mammalian brain and transmit timing information to different regions of the brain and body, coordinating the circadian rhythms of various physiological processes. In Drosophila, an important set of circadian output neurons are called pars intercerebralis (PI) neurons, which receive input from specific clock neurons called DN1. These neurons can further be subdivided into functionally and anatomically distinctive anterior (DN1a) and posterior (DN1p) clusters. The neuropeptide diuretic hormones 31 (Dh31) and 44 (Dh44) are the insect neuropeptides known to activate PI neurons to control activity rhythms. However, the neurophysiological basis of how Dh31 and Dh44 affect circadian clock neural coding mechanisms underlying sleep in Drosophila is not well understood. Here, we identify Dh31/Dh44-dependent spike time precision and plasticity in PI neurons. We find that the application of synthesized Dh31 and Dh44 affects membrane potential dynamics of PI neurons in the precise timing of the neuronal firing through their synergistic interaction, possibly mediated by calcium-activated potassium channel conductance. Further, we characterize that Dh31/Dh44 enhances postsynaptic potentials in PI neurons. Together, these results suggest multiplexed neuropeptide-dependent spike time precision and plasticity as circadian clock neural coding mechanisms underlying sleep in Drosophila.

An Electrolyte‐Gated InGaZnO Phototransistor that Emulates Visual Experience‐Dependent Plasticity

AbstractInspired by neurobiological learning rules, bionic devices that simulate the fundamental functions of synapses and neurons provide a highly effective approach to neuromorphic computing. Among various learning rules, the Bienenstock‐Cooper‐Munro (BCM) learning rule can explain the threshold sliding effect of synaptic weight modification in the visual cortex, which is difficult to explain with the classical Hebb's rule. Existing research mainly focuses on exploiting electrical stimulation to implement the BCM rule, while the optical implementation is still unexplored. In this paper, the light‐history‐dependent BCM learning rule is implemented with electrolyte‐gated InGaZnO (IGZO) transistors. The channel conductance can be modulated through light illumination and electrical stimulation. By utilizing the light‐history‐dependent property of the IGZO electrolyte‐gated transistor and following the triplet‐spike‐timing‐dependent plasticity (STDP) rules, the BCM learning rule is successfully emulated in a single device. Moreover, the light‐history‐dependent property enables a variety of bionic vision functions including image edge detection and associative memory. This work provides a paradigm for the novel implementation of the BCM rule and paves the way for further development of machine vision systems.

Exploiting Spatial Ionic Dynamics in Solid-State Organic Electrochemical Transistors for Multi-Tactile Sensing and Processing.

The human nervous system inspires the next generation of sensory and communication systems for robotics, human-machine interfaces (HMIs), biomedical applications, and artificial intelligence. Neuromorphic approaches address processing challenges; however, the vast number of sensors and their large-scale distribution complicate analog data manipulation. Conventional digital multiplexers are limited by complex circuit architecture and high supply voltage. Large sensory arrays further complicate wiring. An 'in-electrolyte computing' platform is presented by integrating organic electrochemical transistors (OECTs) with a solid-state polymer electrolyte. These devices use synapse-like signal transport and spatially dependent bulk ionic doping, achieving over 400 times modulation in channel conductance, allowing discrimination of locally random-access events without peripheral circuitry or address assignment. It demonstrates information processing from 12 tactile sensors with a single OECT output, showing clear advantages in circuit simplicity over existing all-electronic, all-digital implementations. This self-multiplexer platform offers exciting prospects for circuit-free integration with sensory arrays for high-quality, large-volume analog signal processing.