In Liquido Computation with Electrochemical Transistors and Mixed Conductors for Intelligent Bioelectronics

Cucchi, Matteo; Parker, Daniela; Stavrinidou, Eleni; Gkoupidenis, Paschalis; Kleemann, Hans

doi:10.1002/adma.202209516

Cited by 5 publications

(3 citation statements)

References 78 publications

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“…As an example of application, we simulated the action of an ionic actuator based on OMIECs embedding ionophores and demonstrated its capability to provide single-neuron synaptic facilitation. These efforts are oriented toward versatile integration with iontronic devices aiming at closing the loop of already existing methodologies for neural recording and computation in-liquido [95].…”

Section: Discussionmentioning

confidence: 99%

Finite-element modeling of neuromodulation via controlled delivery of potassium ions using conductive polymer-coated microelectrodes

Verardo,

Mele,

Selmi

et al. 2024

J. Neural Eng.

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Objective. The controlled delivery of potassium is an interesting neuromodulation modality, being potassium ions involved in shaping neuron excitability, synaptic transmission, network synchronization, and playing a key role in pathological conditions like epilepsy and spreading depression. Despite many successful examples of pre-clinical devices able to influence the extracellular potassium concentration, computational frameworks capturing the corresponding impact on neuronal activity are still missing. Approach. We present a finite-element model describing a PEDOT:PSS-coated microelectrode (herein, simply ionic actuator) able to release potassium and thus modulate the activity of a cortical neuron in an in-vitro-like setting. The dynamics of ions in the ionic actuator, the neural membrane, and the cellular fluids are solved self-consistently. Main results. We showcase the capability of the model to describe on a physical basis the modulation of the intrinsic excitability of the cell and the synaptic transmission following the electro-ionic stimulation produced by the actuator. We consider three case studies for the ionic actuator with different levels of selectivity to potassium: ideal selectivity, no selectivity, and selectivity achieved by embedding ionophores in the polymer backbone. Significance. This work is the first step toward a comprehensive computational framework aimed to investigate novel neuromodulation devices targeting specific ionic species, as well as to optimize their design and performance, in terms of the induced modulation of neural activity.

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Section: Discussionmentioning

confidence: 99%

Finite-element modeling of neuromodulation via controlled delivery of potassium ions using conductive polymer-coated microelectrodes

Verardo,

Mele,

Selmi

et al. 2024

J. Neural Eng.

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“…Using liquid analyte solutions as an electrolyte creates novel avenues for signal processing, such as global sensing and wetware/in‐liquido computing. [ 182 ] This topic is discussed in greater depth in Section 5.2.3.…”

Section: Bio‐inspired Adaptive Sensing and Processingmentioning

confidence: 99%

Brain‐Inspired Organic Electronics: Merging Neuromorphic Computing and Bioelectronics Using Conductive Polymers

Krauhausen,

Coen,

Spolaor

et al. 2023

Adv Funct Materials

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Neuromorphic computing offers the opportunity to curtail the huge energy demands of modern artificial intelligence (AI) applications by implementing computations into new, brain‐inspired computing architectures. However, the lack of fabrication processes able to integrate several computing units into monolithic systems and the need for new, hardware‐tailored training algorithms still limit the scope of application and performance of neuromorphic hardware. Recent advancements in the field of organic transistors present new opportunities for neuromorphic systems and smart sensing applications, thanks to their unique properties such as neuromorphic behavior, low‐voltage operation, and mixed ionic‐electronic conductivity. Organic neuromorphic transistors push the boundaries of energy efficient brain‐inspired hardware AI, facilitating decentralized on‐chip learning and serving as a foundation for the advancement of closed‐loop intelligent systems in the next generation. The biocompatibility and dual ionic‐electronic conductivity of organic materials introduce new prospects for biointegration and bioelectronics. Their ability to sense and regulate biosystems, as well as their neuro‐inspired functions can be combined with neuromorphic computing to create the next‐generation of bioelectronics. These systems will be able to seamlessly interact with biological systems and locally compute biosignals in a relevant matter.

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“…Organic mixed ionic–electronic conductors (OMIECs) – carbon-based materials that can efficiently couple and transport ionic and electronic charges – are key elements for a variety of novel technologies, such as bioelectronic devices, 1 soft robotics, 2 neuromorphic computing, 2,3 and energy storage applications. 4 OMIECs are known to dictate the performance of such applications by presenting a strong influence on the phenomena underlying the device operation and the device figures of merit (FoM).…”

Section: Introductionmentioning

confidence: 99%

Melanin/PEDOT:PSS blend as organic mixed ionic electronic conductor (OMIEC) for sustainable electronics

Nozella,

Lima,

de Oliveira

et al. 2023

Mater. Adv.

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In Liquido Computation with Electrochemical Transistors and Mixed Conductors for Intelligent Bioelectronics

Cited by 5 publications

References 78 publications

Finite-element modeling of neuromodulation via controlled delivery of potassium ions using conductive polymer-coated microelectrodes

Finite-element modeling of neuromodulation via controlled delivery of potassium ions using conductive polymer-coated microelectrodes

Brain‐Inspired Organic Electronics: Merging Neuromorphic Computing and Bioelectronics Using Conductive Polymers

Melanin/PEDOT:PSS blend as organic mixed ionic electronic conductor (OMIEC) for sustainable electronics

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