Organic Neuroelectronics: From Neural Interfaces to Neuroprosthetics

Skin-Mountable Functional Electronic Materials for Bio-Integrated Devices

Skin-mountable electronic materials are being intensively evaluated for use in bio-integrated devices that can mutually interact with the human body. Over the past decade, functional electronic materials inspired by the skin are developed with new functionalities to address the limitations of traditional electronic materials for bio-integrated devices. Herein, the recent progress in skin-mountable functional electronic materials for skin-like electronics is introduced with a focus on five perspectives that entail essential functionalities: stretchability, self-healing ability, biocompatibility, breathability, and biodegradability. All functionalities are advanced with each strategy through rational material designs. The skin-mountable functional materials enable the fabrication of bio-integrated electronic devices, which can lead to new paradigms of electronics combining with the human body.

Multifunctional Conductive Hydrogel Interface for Bioelectronic Recording and Stimulation

The past few decades have witnessed the rapid advancement and broad applications of flexible bioelectronics, in wearable and implantable electronics, brain-computer interfaces, neural science and technology, clinical diagnosis, treatment, etc. It is noteworthy that soft and elastic conductive hydrogels, owing to their multiple similarities with biological tissues in terms of mechanics, electronics, water-rich, and biological functions, have successfully bridged the gap between rigid electronics and soft biology. Multifunctional hydrogel bioelectronics, emerging as a new generation of promising material candidates, have authentically established highly compatible and reliable, high-quality bioelectronic interfaces, particularly in bioelectronic recording and stimulation. This review summarizes the material basis and design principles involved in constructing hydrogel bioelectronic interfaces, and systematically discusses the fundamental mechanism and unique advantages in bioelectrical interfacing with the biological surface. Furthermore, an overview of the state-of-the-art manufacturing strategies for hydrogel bioelectronic interfaces with enhanced biocompatibility and integration with the biological system is presented. This review finally exemplifies the unprecedented advancement and impetus toward bioelectronic recording and stimulation, especially in implantable and integrated hydrogel bioelectronic systems, and concludes with a perspective expectation for hydrogel bioelectronics in clinical and biomedical applications.

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.

Organic Mixed Ionic-Electronic Conductors for Bioelectronic Sensors: Materials and Operation Mechanisms

The field of organic mixed ionic-electronic conductors (OMIECs) has gained significant attention due to their ability to transport both electrons and ions, making them promising candidates for various applications. Initially focused on inorganic materials, the exploration of mixed conduction has expanded to organic materials, especially polymers, owing to their advantages such as solution processability, flexibility, and property tunability. OMIECs, particularly in the form of polymers, possess both electronic and ionic transport functionalities. This review provides an overview of OMIECs in various aspects covering mechanisms of charge transport including electronic transport, ionic transport, and ionic-electronic coupling, as well as conducting/semiconducting conjugated polymers and their applications in organic bioelectronics, including (multi)sensors, neuromorphic devices, and electrochromic devices. OMIECs show promise in organic bioelectronics due to their compatibility with biological systems and the ability to modulate electronic conduction and ionic transport, resembling the principles of biological systems. Organic electrochemical transistors (OECTs) based on OMIECs offer significant potential for bioelectronic applications, responding to external stimuli through modulation of ionic transport. An in-depth review of recent research achievements in organic bioelectronic applications using OMIECs, categorized based on physical and chemical stimuli as well as neuromorphic devices and circuit applications, is presented.

Evolution of Musculoskeletal Electronics

The musculoskeletal system, constituting the largest human physiological system, plays a critical role in providing structural support to the body, facilitating intricate movements, and safeguarding internal organs. By virtue of advancements in revolutionized materials and devices, particularly in the realms of motion capture, health monitoring, and postoperative rehabilitation, "musculoskeletal electronics" has actually emerged as an infancy area, but has not yet been explicitly proposed. In this review, the concept of musculoskeletal electronics is elucidated, and the evolution history, representative progress, and key strategies of the involved materials and state-of-the-art devices are summarized. Therefore, the fundamentals of musculoskeletal electronics and key functionality categories are introduced. Subsequently, recent advances in musculoskeletal electronics are presented from the perspectives of "in vitro" to "in vivo" signal detection, interactive modulation, and therapeutic interventions for healing and recovery. Additionally, nine strategy avenues for the development of advanced musculoskeletal electronic materials and devices are proposed. Finally, concise summaries and perspectives are proposed to highlight the directions that deserve focused attention in this booming field.

An organic brain-inspired platform with neurotransmitter closed-loop control, actuation and reinforcement learning

Organic neuromorphic platforms have recently received growing interest for the implementation and integration of artificial and hybrid neuronal networks. Here, achieving closed-loop and learning/training processes as in the human brain is still a major challenge especially exploiting time-dependent biosignalling such as neurotransmitter release. Here, we present an integrated organic platform capable of cooperating with standard silicon technologies, to achieve brain-inspired computing via adaptive synaptic potentiation and depression, in a closed-loop fashion. The microfabricated platform could be interfaced and control a robotic hand which ultimately was able to learn the grasping of differently sized objects, autonomously.

Understanding asymmetric switching times in accumulation mode organic electrochemical transistors

Understanding the factors underpinning device switching times is crucial for the implementation of organic electrochemical transistors in neuromorphic computing, bioelectronics and real-time sensing applications. Existing models of device operation cannot explain the experimental observations that turn-off times are generally much faster than turn-on times in accumulation mode organic electrochemical transistors. Here, using operando optical microscopy, we image the local doping level of the transistor channel and show that turn-on occurs in two stages-propagation of a doping front, followed by uniform doping-while turn-off occurs in one stage. We attribute the faster turn-off to a combination of engineering as well as physical and chemical factors including channel geometry, differences in doping and dedoping kinetics and the phenomena of carrier-density-dependent mobility. We show that ion transport limits the operation speed in our devices. Our study provides insights into the kinetics of organic electrochemical transistors and guidelines for engineering faster organic electrochemical transistors.

Injectable Fluorescent Neural Interfaces for Cell-Specific Stimulating and Imaging

Building on current explorations in chronic optical neural interfaces, it is essential to address the risk of photothermal damage in traditional optogenetics. By focusing on calcium fluorescence for imaging rather than stimulation, injectable fluorescent neural interfaces significantly minimize photothermal damage and improve the accuracy of neuronal imaging. Key advancements including the use of injectable microelectronics for targeted electrical stimulation and their integration with cell-specific genetically encoded calcium indicators have been discussed. These injectable electronics that allow for post-treatment retrieval offer a minimally invasive solution, enhancing both usability and reliability. Furthermore, the integration of genetically encoded fluorescent calcium indicators with injectable bioelectronics enables precise neuronal recording and imaging of individual neurons. This shift not only minimizes risks such as photothermal conversion but also boosts safety, specificity, and effectiveness of neural imaging. Embracing these advancements represents a significant leap forward in biomedical engineering and neuroscience, paving the way for advanced brain-machine interfaces.

A modular organic neuromorphic spiking circuit for retina-inspired sensory coding and neurotransmitter-mediated neural pathways

Signal communication mechanisms within the human body rely on the transmission and modulation of action potentials. Replicating the interdependent functions of receptors, neurons and synapses with organic artificial neurons and biohybrid synapses is an essential first step towards merging neuromorphic circuits and biological systems, crucial for computing at the biological interface. However, most organic neuromorphic systems are based on simple circuits which exhibit limited adaptability to both external and internal biological cues, and are restricted to emulate only specific the functions of an individual neuron/synapse. Here, we present a modular neuromorphic system which combines organic spiking neurons and biohybrid synapses to replicate a neural pathway. The spiking neuron mimics the sensory coding function of afferent neurons from light stimuli, while the neuromodulatory activity of interneurons is emulated by neurotransmitters-mediated biohybrid synapses. Combining these functions, we create a modular connection between multiple neurons to establish a pre-processing retinal pathway primitive.

Recent advancements in implantable neural links based on organic synaptic transistors

The progress of brain synaptic devices has witnessed an era of rapid and explosive growth. Because of their integrated storage, excellent plasticity and parallel computing, and system information processing abilities, various field effect transistors have been used to replicate the synapses of a human brain. Organic semiconductors are characterized by simplicity of processing, mechanical flexibility, low cost, biocompatibility, and flexibility, making them the most promising materials for implanted brain synaptic bioelectronics. Despite being used in numerous intelligent integrated circuits and implantable neural linkages with multiple terminals, organic synaptic transistors still face many obstacles that must be overcome to advance their development. A comprehensive review would be an excellent tool in this respect. Therefore, the latest advancements in implantable neural links based on organic synaptic transistors are outlined. First, the distinction between conventional and synaptic transistors are highlighted. Next, the existing implanted organic synaptic transistors and their applicability to the brain as a neural link are summarized. Finally, the potential research directions are discussed.

Hydrogel-Gated FETs in Neuromorphic Computing to Mimic Biological Signal: A Review

Hydrogel-gated synaptic transistors offer unique advantages, including biocompatibility, tunable electrical properties, being biodegradable, and having an ability to mimic biological synaptic plasticity. For processing massive data with ultralow power consumption due to high parallelism and human brain-like processing abilities, synaptic transistors have been widely considered for replacing von Neumann architecture-based traditional computers due to the parting of memory and control units. The crucial components mimic the complex biological signal, synaptic, and sensing systems. Hydrogel, as a gate dielectric, is the key factor for ionotropic devices owing to the excellent stability, ultra-high linearity, and extremely low operating voltage of the biodegradable and biocompatible polymers. Moreover, hydrogel exhibits ionotronic functions through a hybrid circuit of mobile ions and mobile electrons that can easily interface between machines and humans. To determine the high-efficiency neuromorphic chips, the development of synaptic devices based on organic field effect transistors (OFETs) with ultra-low power dissipation and very large-scale integration, including bio-friendly devices, is needed. This review highlights the latest advancements in neuromorphic computing by exploring synaptic transistor developments. Here, we focus on hydrogel-based ionic-gated three-terminal (3T) synaptic devices, their essential components, and their working principle, and summarize the essential neurodegenerative applications published recently. In addition, because hydrogel-gated FETs are the crucial members of neuromorphic devices in terms of cutting-edge synaptic progress and performances, the review will also summarize the biodegradable and biocompatible polymers with which such devices can be implemented. It is expected that neuromorphic devices might provide potential solutions for the future generation of interactive sensation, memory, and computation to facilitate the development of multimodal, large-scale, ultralow-power intelligent systems.

A Diffusive Artificial Synapse Based on Charged Metal Nanoparticles

We show that a diffusive memristor with analogue switching characteristics can be achieved in a layer of gold nanoparticles (AuNPs) functionalized with charged self-assembled monolayers (deprotonated 11-mercaptoundecanoic acid). The nanoparticle core and the anchored stationary charges are jammed within the layer while the mobile counterions [N(CH3)4+] can respond to the electric field and spontaneously diffuse back to the initial positions upon removal of the field. This metal nanoparticle device is set-step free, energy consumption efficient, mechanically flexible, and analogous to bio-Ca2+ dynamics and has tunable conductance modulation capabilities at the counterion concentrations. The gradual resistive switching behavior enables us to implement several important synaptic functions such as potentiation/depression, spike voltage-dependent plasticity, spike duration-dependent plasticity, spike frequency-dependent plasticity, and paired-pulse facilitation. Finally, on the basis of the paired-pulse facilitation characteristics, the metal nanoparticle diffusive artificial synapse is used for edge extraction with exhibits excellent performance.

Neuromorphic hardware for somatosensory neuroprostheses

In individuals with sensory-motor impairments, missing limb functions can be restored using neuroprosthetic devices that directly interface with the nervous system. However, restoring the natural tactile experience through electrical neural stimulation requires complex encoding strategies. Indeed, they are presently limited in effectively conveying or restoring tactile sensations by bandwidth constraints. Neuromorphic technology, which mimics the natural behavior of neurons and synapses, holds promise for replicating the encoding of natural touch, potentially informing neurostimulation design. In this perspective, we propose that incorporating neuromorphic technologies into neuroprostheses could be an effective approach for developing more natural human-machine interfaces, potentially leading to advancements in device performance, acceptability, and embeddability. We also highlight ongoing challenges and the required actions to facilitate the future integration of these advanced technologies.

Towards Artificial Visual Sensory System: Organic Optoelectronic Synaptic Materials and Devices

Developing an artificial visual sensory system requires optoelectronic materials and devices that can mimic the behavior of biological synapses. Organic/polymeric semiconductors have emerged as promising candidates for optoelectronic synapses due to their tunable optoelectronic properties, mechanic flexibility, and biological compatibility. In this review, we discuss the recent progress in organic optoelectronic synaptic materials and devices, including their design principles, working mechanisms, and applications. We also highlight the challenges and opportunities in this field and provide insights into potential applications of these materials and devices in next-generation artificial visual systems. By leveraging the advances in organic optoelectronic materials and devices, we can envision its future development in artificial intelligence.

Cascade-heterogated biphasic gel iontronics for electronic-to-multi-ionic signal transmission

Currently, electronics and iontronics in abiotic-biotic systems can only use electrons and single-species ions as unitary signal carriers. Thus, a mechanism of gating transmission for multiple biosignals in such devices is needed to match and modulate complex aqueous-phase biological systems. Here we report the use of cascade-heterogated biphasic gel iontronics to achieve diverse electronic-to-multi-ionic signal transmission. The cascade-heterogated property determined the transfer free energy barriers experienced by ions and ionic hydration-dehydration states under an electric potential field, fundamentally enhancing the distinction of cross-interface transmission between different ions by several orders of magnitude. Such heterogated or chemical-heterogated iontronics with programmable features can be coupled with multi-ion cross-interface mobilities for hierarchical and selective cross-stage signal transmission. We expect that such iontronics would be ideal candidates for a variety of biotechnology applications.

Tailoring Wavelength-Adaptive Visual Neuroplasticity Transitions of Synaptic Transistors Comprising Rod-Coil Block Copolymers for Dual-Mode Photoswitchable Learning/Forgetting Neural Functions

The vision-inspired artificial neural network based on optical synapses has drawn a tremendous amount of attention for emulating biological senses. Although photoexcitation-induced synaptic functionalities have been widely studied, optical habituation via the photoinhibitory pathway is yet to be demonstrated for sophisticated biomimetic visual adaptive systems. Here, the first optical neuromorphic block copolymer (BCP) phototransistor is demonstrated as an all-optical operation responding to various wavelengths, fulfilling photoassisted dynamic learning/forgetting cycles via optical potentiation without gate bias. The polyfluorene BCPs were precisely designed to enable wavelength-adaptive responses, benefiting from interfacial semiconductor/electret morphology and the crystallinity/electron affinity of the BCPs. Notably, this is the first work to simultaneously exhibit fully light-controlled short- and long-term memory based on organic material systems. The device presents a high current contrast above 100-fold and long-term retention over 104 s. As a proof-of-concept for neural networks, a 6 × 6 array of photosynapses performed outstanding visual pattern learning/forgetting with high accuracy. This study exploits the design strategy of a conjugated BCP electret to unleash the full potential of wavelength-adaptive visual neuroplasticity transitions. It provides an effective architecture for designing high-performance and high-storage capacity required applications in next-generation neuromorphic systems.

Helical Nanofiber Photoelectric Synaptic Devices for an Artificial Vision Nervous System

Inspired by the helical structure and the resultant exquisite functions of biomolecules, helical polymers have received increasing attention. Here, a series of poly(3-hexylthiophene)-block-poly(phenyl isocyanide) (P3HT-b-PPI) copolymers were prepared using a simple one-pot living polymerization method. Interestingly, the P3HT80-b-PPI30 films were found to have a helical nanofiber structure. The corresponding device has superior optoelectronic properties, such as a broadened spectral response range from the visible band to the deep ultraviolet (DUV) and an approximately 5-fold longer carrier decay time after DUV light stimulation. An energy consumption of 1.44 fJ per synaptic event was obtained, which is the lowest energy consumption achieved so far with DUV light stimulation. The encryption and decryption of images are implemented using an array of devices. Finally, a photoreceptor neural pathway was constructed to achieve early warning for the recognition of the display of harmful light. This research provides an effective strategy for the development of a novel optoelectronic synaptic device.

Flexible and Stretchable Electrochemical Sensors for Biological Monitoring

The rise of flexible and stretchable electronics has revolutionized biosensor techniques for probing biological systems. Particularly, flexible and stretchable electrochemical sensors (FSECSs) enable the in situ quantification of numerous biochemical molecules in different biological entities owing to their exceptional sensitivity, fast response, and easy miniaturization. Over the past decade, the fabrication and application of FSECSs have significantly progressed. This review highlights key developments in electrode fabrication and FSECSs functionalization. It delves into the electrochemical sensing of various biomarkers, including metabolites, electrolytes, signaling molecules, and neurotransmitters from biological systems, encompassing the outer epidermis, tissues/organs in vitro and in vivo, and living cells. Finally, considering electrode preparation and biological applications, current challenges and future opportunities for FSECSs are discussed.

Quantum Topological Neuristors for Advanced Neuromorphic Intelligent Systems

Neuromorphic artificial intelligence systems are the future of ultrahigh performance computing clusters to overcome complex scientific and economical challenges. Despite their importance, the advancement in quantum neuromorphic systems is slow without specific device design. To elucidate biomimicking mammalian brain synapses, a new class of quantum topological neuristors (QTN) with ultralow energy consumption (pJ) and higher switching speed (µs) is introduced. Bioinspired neural network characteristics of QTNs are the effects of edge state transport and tunable energy gap in the quantum topological insulator (QTI) materials. With augmented device and QTI material design, top notch neuromorphic behavior with effective learning-relearning-forgetting stages is demonstrated. Critically, to emulate the real-time neuromorphic efficiency, training of the QTNs is demonstrated with simple hand gesture game by interfacing them with artificial neural networks to perform decision-making operations. Strategically, the QTNs prove the possession of incomparable potential to realize next-gen neuromorphic computing for the development of intelligent machines and humanoids.

Organic Electrochemical Transistor Immuno-Sensors for Spike Protein Early Detection

The global COVID-19 pandemic has had severe consequences from the social and economic perspectives, compelling the scientific community to focus on the development of effective diagnostics that can combine a fast response and accurate sensitivity/specificity performance. Presently available commercial antigen-detecting rapid diagnostic tests (Ag-RDTs) are very fast, but still face significant criticisms, mainly related to their inability to amplify the protein signal. This translates to a limited sensitive outcome and, hence, a reduced ability to hamper the spread of SARS-CoV-2 infection. To answer the urgent need for novel platforms for the early, specific and highly sensitive detection of the virus, this paper deals with the use of organic electrochemical transistors (OECTs) as very efficient ion-electron converters and amplifiers for the detection of spike proteins and their femtomolar concentration. The electrical response of the investigated OECTs was carefully analyzed, and the changes in the parameters associated with the transconductance (i.e., the slope of the transfer curves) in the gate voltage range between 0 and 0.3 V were found to be more clearly correlated with the spike protein concentration. Moreover, the functionalization of OECT-based biosensors with anti-spike and anti-nucleocapside proteins, the major proteins involved in the disease, demonstrated the specificity of these devices, whose potentialities should also be considered in light of the recent upsurge of the so-called "long COVID" syndrome.

Direct-print three-dimensional electrodes for large- scale, high-density, and customizable neural inter- faces

Silicon-based planar microelectronics is a powerful tool for scalably recording and modulating neural activity at high spatiotemporal resolution, but it remains challenging to target neural structures in three dimensions (3D). We present a method for directly fabricating 3D arrays of tissue-penetrating microelectrodes onto silicon microelectronics. Leveraging a high-resolution 3D printing technology based on 2-photon polymerization and scalable microfabrication processes, we fabricated arrays of 6,600 microelectrodes 10-130 μm tall and at 35-μm pitch onto a planar silicon-based microelectrode array. The process enables customizable electrode shape, height and positioning for precise targeting of neuron populations distributed in 3D. As a proof of concept, we addressed the challenge of specifically targeting retinal ganglion cell (RGC) somas when interfacing with the retina. The array was customized for insertion into the retina and recording from somas while avoiding the axon layer. We verified locations of the microelectrodes with confocal microscopy and recorded high-resolution spontaneous RGC activity at cellular resolution. This revealed strong somatic and dendritic components with little axon contribution, unlike recordings with planar microelectrode arrays. The technology could be a versatile solution for interfacing silicon microelectronics with neural structures and modulating neural activity at large scale with single-cell resolution.

Ferroelectret nanogenerators for the development of bioengineering systems

Bioengineering devices and systems will become a practical and versatile technology in society when sustainability issues, primarily pertaining to their efficiency, sustainability, and human-machine interaction, are fully addressed. It has become evident that technological paths should not rely on a single operation mechanism but instead on holistic methodologies that integrate different phenomena and approaches with complementary advantages. As an intriguing invention, the ferroelectret nanogenerator (FENG) has emerged with promising potential in various fields of bioengineering. Utilizing the changes in the engineered macro-scale electric dipoles to create displacement current (and vice versa), FENGs have been demonstrated to be a compelling strategy for bidirectional conversion of energy between the electrical and mechanical domains. Here we provide a comprehensive overview of the latest advancements in integrating FENGs in bioengineering systems, focusing on the applications with the most potential and the underlying current constraints.

Advanced materials for implantable neuroelectronics

Materials innovation has arguably played one of the most important roles in the development of implantable neuroelectronics. Such technologies explore biocompatible working systems for reading, triggering, and manipulating neural signals for neuroscience research and provide the additional potential to develop devices for medical diagnostics and/or treatment. The past decade has witnessed a golden era in neuroelectronic materials research. For example, R&D on soft material-based devices have exploded and taken center stage for many applications, including both central and peripheral nerve interfaces. Recent developments have also witnessed the emergence of biodegradable and multifunctional devices. In this article, we aim to overview recent advances in implantable neuroelectronics with an emphasis on chronic biocompatibility, biodegradability, and multifunctionality. In addition to highlighting fundamental materials innovations, we also discuss important challenges and future opportunities.

Technology Roadmap for Flexible Sensors

Humans rely increasingly on sensors to address grand challenges and to improve quality of life in the era of digitalization and big data. For ubiquitous sensing, flexible sensors are developed to overcome the limitations of conventional rigid counterparts. Despite rapid advancement in bench-side research over the last decade, the market adoption of flexible sensors remains limited. To ease and to expedite their deployment, here, we identify bottlenecks hindering the maturation of flexible sensors and propose promising solutions. We first analyze challenges in achieving satisfactory sensing performance for real-world applications and then summarize issues in compatible sensor-biology interfaces, followed by brief discussions on powering and connecting sensor networks. Issues en route to commercialization and for sustainable growth of the sector are also analyzed, highlighting environmental concerns and emphasizing nontechnical issues such as business, regulatory, and ethical considerations. Additionally, we look at future intelligent flexible sensors. In proposing a comprehensive roadmap, we hope to steer research efforts towards common goals and to guide coordinated development strategies from disparate communities. Through such collaborative efforts, scientific breakthroughs can be made sooner and capitalized for the betterment of humanity.