A Flexible Organic Electrochemical Synaptic Transistor With Dopamine-Mediated Plasticity

Qian, Jie; Cao, Jie; Liu, Xusheng; Chen, Pei; Gao, Feng; Zhang, Xumeng; Wang, Ming; Liu, Qi

doi:10.1109/led.2022.3225143

Cited by 18 publications

(11 citation statements)

References 23 publications

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“…An artificial synapse emulates the characteristics of a biological synapse, such as long-term and short-term plasticity modulated by spike inputs, enabling memorization, learning, adaptation, and other biological computational capabilities. Currently reported artificial synapses are modulated by diverse stimuli such as electrical input, light, , chemicals (neurotransmitters), − temperature, and combinations of the above ( e.g. , electrical and optical inputs , ).…”

Section: Discussionmentioning

confidence: 99%

Technology Roadmap for Flexible Sensors

et al. 2023

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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.

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Section: Discussionmentioning

confidence: 99%

Technology Roadmap for Flexible Sensors

et al. 2023

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“…With the advent of inorganic and organic neuromorphic devices, which consist of circuit elements capable of changing for example their conductance, and thereby the efficacy to which they inject charge into the neurons, we envision the possibility of encoding the learned stimulation paradigms by directly integrating RL algorithms into a neuromorphic architectures that could regulate the activity of neural networks in a closed‐loop fashion while requiring very low power to do so as well as implementing network level operations [ 105 ] and ultimately being integrated into soft substrates. [ 106 ] Moreover, organic neuromorphic platforms have also recently achieved functional hybrid coupling with biological counterparts both in vitro and in vivo featuring short and long term plasticity through neurotransmitter modulation. [ 107 ] Such integrated, intelligent neural interfaces could be powerful tools for regulating pathological neural activity patterns for example, in Parkinson's disease or epilepsy.…”

Section: Next Generation Devicesmentioning

confidence: 99%

Toward the Next Generation of Neural Iontronic Interfaces

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et al. 2023

Adv Healthcare Materials

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Neural interfaces are evolving at a rapid pace owing to advances in material science and fabrication, reduced cost of scalable complementary metal oxide semiconductor (CMOS) technologies, and highly interdisciplinary teams of researchers and engineers that span a large range from basic to applied and clinical sciences. This study outlines currently established technologies, defined as instruments and biological study systems that are routinely used in neuroscientific research. After identifying the shortcomings of current technologies, such as a lack of biocompatibility, topological optimization, low bandwidth, and lack of transparency, it maps out promising directions along which progress should be made to achieve the next generation of symbiotic and intelligent neural interfaces. Lastly, it proposes novel applications that can be achieved by these developments, ranging from the understanding and reproduction of synaptic learning to live‐long multimodal measurements to monitor and treat various neuronal disorders.

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“…The process in question is a basic aspect that underlies the acquisition of knowledge and the retention of information inside biological neural systems. 218…”

Section: Electrochemical-memristor-based Artificial Neurons and Synapsesmentioning

confidence: 99%