Opportunities and dilemmas of<i>in vitro</i>nano neural electrodes

Wu, Yu; Chen, Haowen; Guo, Liang

doi:10.1039/c9ra08917a

Cited by 15 publications

(24 citation statements)

References 88 publications

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“…Recently, the application of nanotechnology on neuronal electrophysiology has brought about a promising solution to overcome this limitation and to fabricate devices that are capable of detecting sub-threshold potential (Liu et al, 2017;Wei et al, 2018;Yoo et al, 2020). Although substantial engineering issues remain before the potential of nano-neural interfaces can be fully exploited (Wu et al, 2020), the future application of our algorithm to more sensitive recordings appear to be a promising approach for a more accurate understanding of network connectivity as a consequence of synaptic and extra-synaptic inputs as well as subthreshold potentials in both physiological and pathological conditions.…”

Section: Discussionmentioning

confidence: 99%

Super-Selective Reconstruction of Causal and Direct Connectivity With Application to in vitro iPSC Neuronal Networks

et al. 2021

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Despite advancements in the development of cell-based in-vitro neuronal network models, the lack of appropriate computational tools limits their analyses. Methods aimed at deciphering the effective connections between neurons from extracellular spike recordings would increase utility of in vitro local neural circuits, especially for studies of human neural development and disease based on induced pluripotent stem cells (hiPSC). Current techniques allow statistical inference of functional couplings in the network but are fundamentally unable to correctly identify indirect and apparent connections between neurons, generating redundant maps with limited ability to model the causal dynamics of the network. In this paper, we describe a novel mathematically rigorous, model-free method to map effective—direct and causal—connectivity of neuronal networks from multi-electrode array data. The inference algorithm uses a combination of statistical and deterministic indicators which, first, enables identification of all existing functional links in the network and then reconstructs the directed and causal connection diagram via a super-selective rule enabling highly accurate classification of direct, indirect, and apparent links. Our method can be generally applied to the functional characterization of any in vitro neuronal networks. Here, we show that, given its accuracy, it can offer important insights into the functional development of in vitro hiPSC-derived neuronal cultures.

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Section: Discussionmentioning

confidence: 99%

Super-Selective Reconstruction of Causal and Direct Connectivity With Application to in vitro iPSC Neuronal Networks

et al. 2021

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“…Although NW‐sensor diagnosis systems are at their early stages of development, nanoneedle‐based approaches to disease and cancer treatment are still at the experimental stage. Nevertheless, promising results have been reported using nanoneedles for primary neuron and neurological applications, [ 11,76d,111 ] treatment of retinal disorders, [ 112 ] and regeneration of damaged tissues. [ 113 ]…”

Section: Vertical Nanoneedles In Clinical Applicationsmentioning

confidence: 99%

“…Electrogenic neurons are the control units of most biological living beings; they can sense diverse stimuli (mechanical, chemical, and thermal), and deliver accurate commands through neuromuscular junctions. [ 11 ] With the great potential in life technologies and artificial intelligence, it has long been a major pursuit in neuroscience, bioengineering, and electrical engineering to develop seamless neural interfaces for probing, understanding, and modulating neural activities. Recent advances in NW technology have brought about a promising solution to achieve precise and localized interrogations in neuronal electrophysiology [76d,114] .…”

Section: Vertical Nanoneedles In Clinical Applicationsmentioning

confidence: 99%

“…[ 10 ] Trying to replicate what nature is excellent at doing using advanced micro and nanotechnologies has been proven really effective and the way to move the field forward. For example, nanoparticles with virus‐like sizes and properties have resulted in effective nanocarriers for gene and drug delivery; nanoneedles can emulate the perfect mechanical, chemical, and electrical cues to trigger neuronal responses [ 11 ] ; and OOC technologies aim to replicate natural processes found in our bodies. [ 12 ] But, the field does not stop here.…”

Section: Introductionmentioning

confidence: 99%

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Engineering Micro–Nanomaterials for Biomedical Translation

Chen

Alba

Tieu

et al. 2021

Advanced NanoBiomed Research

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Engineered nano–bio interfaces–driven by vertical micro/nanoneedles, nanoparticles, organ‐on‐chip devices, and a diversity of nanosubstrates for mass spectroscopy imaging–are spurring scientific and technological progress, from fundamental to transnational biomedical research. Each class has its own characteristic features, which is critical for their translational uptake, but they broadly share the same range of functionality and applicability at the forefront of modern research and medicine. The review provides insights into unique attributes of microneedle technology and its ability for efficient transdermal transport of therapeutic compounds. The uses of nanoneedle technology in precise manipulation of increasingly complex cellular processes at the cell–material interface and their potential for major improvements for many fundamental research applications and ex vivo cell‐based therapies are highlighted. A snapshot in the use of food and drug administration (FDA)‐approved nanoparticle therapeutics and their applications in nanomedicine is provided. The achievements in organ‐on‐chip technology, particularly at the preclinical stage, and its potential to efficiently screen diverse types of therapeutics are covered. The final section is dedicated to the use of nanomaterial‐enhanced mass spectrometry in drug discovery and imaging. Overall, this review aims to highlight those main rules in the design of bio–nano interfaces that have successfully achieved translation into the market.

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“…Recently, the application of nanotechnology on neuronal electrophysiology has brought about a promising solution to overcome this limitation and to fabricate devices that are capable of detecting sub-threshold potential [32,77,81]. Although substantial engineering issues remain before the potential of nano neural interfaces can be fully exploited [79], the future application of our algorithm to more sensitive recordings appear to be a promising approach for a more accurate understanding of network connectivity as a consequence of synaptic and extra-synaptic inputs as well as subthreshold potentials in both physiological and pathological conditions.…”

Section: Importantly In This Work We Did Not Attempt To Simulate Andmentioning

confidence: 99%

Super-selective reconstruction of causal and direct connectivity with application toin-vitroiPSC neuronal networks

Puppo

PrÐ

Bang

et al. 2020

Preprint

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Despite advancements in the development of cell-based in-vitro neuronal network models, the lack of appropriate computational tools limits their analyses. Methods aimed at deciphering the effective connections between neurons from extracellular spike recordings would increase utility of in-vitro local neural circuits, especially for studies of human neural development and disease based on induced pluripotent stem cells (hiPSC). Current techniques allow statistical inference of functional couplings in the network but are fundamentally unable to correctly identify indirect and apparent connections between neurons, generating redundant maps with limited ability to model the causal dynamics of the network. In this paper, we describe a novel mathematically rigorous, model-free method to map effective -direct and causal -connectivity of neuronal networks from multi-electrode array data. The inference algorithm uses a combination of statistical and deterministic indicators which, first, enables identification of all existing functional links in the network and then, reconstructs the directed and causal connection diagram via a super-selective rule enabling highly accurate classification of direct, indirect and apparent links. Our method can be generally applied to the functional characterization of any in-vitro neuronal networks. Here, we show that, given its accuracy, it can offer important insights into the functional development of in-vitro iPSC-derived neuronal cultures by reconstructing their effective connectivity, thus facilitating future efforts to generate predictive models for neurological disorders, drug testing and neuronal network modeling.

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Opportunities and dilemmas ofin vitronano neural electrodes

Abstract: Developing electrophysiological platforms to capture electrical activities of neurons and exert modulatory stimuli lays the foundation for many neuroscience-related disciplines, including the neuron–machine interface, neuroprosthesis, and mapping of brain circuitry.

Cited by 15 publications

References 88 publications

Super-Selective Reconstruction of Causal and Direct Connectivity With Application to in vitro iPSC Neuronal Networks

Super-Selective Reconstruction of Causal and Direct Connectivity With Application to in vitro iPSC Neuronal Networks

Engineering Micro–Nanomaterials for Biomedical Translation

Super-selective reconstruction of causal and direct connectivity with application toin-vitroiPSC neuronal networks

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