Recent advances in neural dust: towards a neural interface platform

Neely, Ryan; Piech, David K.; Santacruz, Samantha R.; Maharbiz, Michel M.; Carmena, Jose M.

doi:10.1016/j.conb.2017.12.010

Cited by 89 publications

(46 citation statements)

References 16 publications

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“…So far, neural dust has only been demonstrated in vivo in the peripheral nervous system, specifically the sciatic nerve, in a millimeter-scale device. [46,117] The neural dust "mote" consists of a 50 µm thick polyimide flexible printed circuit board upon which a piezocrystal and custom transistor are attached using conductive silver paste to aluminum wirebonds and conductive gold traces (Figure 7). [28] Ultrasonic energy attenuates less than electromagnetic (EM) radiation in tissue; [28] however, the cranial bone dampens ultrasonic waves considerably through absorption, reflection, scattering, and mode conversion.…”

Section: Neural Dustmentioning

confidence: 99%

“…Shrinking the piezocrystal would, therefore, degrade the signal-to-noise ratio of the backscatter link. [117] While neural dust provides a step toward a desirable form factor, much work remains to be done to achieve further miniaturization of a wireless neuroimplantable device that can accomplish transcranial communication and power transfer at safe energy levels.…”

Section: Neural Dustmentioning

confidence: 99%

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The Future of Neuroimplantable Devices: A Materials Science and Regulatory Perspective

2019

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The past two decades have seen unprecedented progress in the development of novel materials, form factors, and functionalities in neuroimplantable technologies, including electrocorticography (ECoG) systems, multielectrode arrays (MEAs), Stentrode, and deep brain probes. The key considerations for the development of such devices intended for acute implantation and chronic use, from the perspective of biocompatible hybrid materials incorporation, conformable device design, implantation procedures, and mechanical and biological risk factors, are highlighted. These topics are connected with the role that the U.S. Food and Drug Administration (FDA) plays in its regulation of neuroimplantable technologies based on the above parameters. Existing neuroimplantable devices and efforts to improve their materials and implantation protocols are first discussed in detail. The effects of device implantation with regards to biocompatibility and brain heterogeneity are then explored. Topics examined include brain‐specific risk factors, such as bacterial infection, tissue scarring, inflammation, and vasculature damage, as well as efforts to manage these dangers through emerging hybrid, bioelectronic device architectures. The current challenges of gaining clinical approval by the FDA—in particular, with regards to biological, mechanical, and materials risk factors—are summarized. The available regulatory pathways to accelerate next‐generation neuroimplantable devices to market are then discussed.

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Section: Neural Dustmentioning

confidence: 99%

Section: Neural Dustmentioning

confidence: 99%

The Future of Neuroimplantable Devices: A Materials Science and Regulatory Perspective

2019

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“…If this progress in data analysis will be complemented by substantial improvement in our measurement methods, for example with intracortical microelectrode grids that measure EEG directly from the cortical surface or, as yet unproven methods such as "neural dust" (a system of intracortical nanoparticles and ultrasound) (Neely et al, 2018), we can expect substantial further progress in the types and amounts of information that can be extracted from neurotechnological measurements.…”

Section: Intrusive Ai and The Protection Of Brain Data Mental Privacmentioning

confidence: 99%

Artificial Intelligence in Basic and Clinical Neuroscience: Opportunities and Ethical Challenges

Kellmeyer

2019

Neuroforum

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The analysis of large amounts of personal data with artificial neural networks for deep learning is the driving technology behind new artificial intelligence (AI) systems for all areas in science and technology. These AI methods have evolved from applications in computer vision, the automated analysis of images, and now include frameworks and methods for analyzing multimodal datasets that combine data from many different source, including biomedical devices, smartphones and common user behavior in cyberspace. For neuroscience, these widening streams of personal data and machine learning methods provide many opportunities for basic data-driven research as well as for developing new tools for diagnostic, predictive and therapeutic applications for disorders of the nervous system. The increasing automation and autonomy of AI systems, however, also creates substantial ethical challenges for basic research and medical applications. Here, scientific and medical opportunities as well ethical challenges are summarized and discussed.

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“…One of the main issues to overcome is the different opacity of the brain tissue and the skull to the diverse electromagnetic probe that can be used to connect the brain with external devices or with other people. Recently, interesting solutions have been proposed by a group from Stanford introducing the neural dust [182], an ultrasonic communication system based on subdural transceivers and multiple tiny motes directly implanted in the brain. Probably a viable method is the distribution of various technologies through the layer of the head: we can think to tattoo electronics on the skin to fabricate antennas and communication modules and insert infrared or magnetic source inside the skull to stimulate neurons.…”

Section: Future Perspective About Brain Neural Interfacementioning

confidence: 99%

The rise of flexible electronics in neuroscience, from materials selection to in vitro and in vivo applications

Maiolo

Polese

Convertino

2019

Advances in Physics: X

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Neuroscience deals with one of the most complicate system we can study: the brain. The huge amount of connections among the cells and the different phenomena occurring at different scale give rise to a continuous flow of data that have to be collected, analyzed and interpreted. Neuroscientists try to interrogate this complexity to find basic principles underlying brain electrochemical signalling and human/animal behaviour to disclose the mechanisms that trigger neurodegenerative diseases and to understand how restoring damaged brain circuits. The main tool to perform these tasks is a neural interface, a system able to interact with brain tissue at different levels to provide a uni/bidirectional communication path. Recently, breakthroughs coming from various disciplines have been combined to enforce features and potentialities of neural interfaces. Among the different findings, flexible electronics is playing a pivotal role in revolutionizing neural interfaces. In this work, we review the most recent advances in the fabrication of neural interfaces based on flexible electronics. We define challenges and issues to be solved for the application of such platforms and we discuss the different parts of the system regarding improvements in materials selection and breakthrough in applications both for in vitro and in vivo tests.

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Recent advances in neural dust: towards a neural interface platform

Cited by 89 publications

References 16 publications

The Future of Neuroimplantable Devices: A Materials Science and Regulatory Perspective

The Future of Neuroimplantable Devices: A Materials Science and Regulatory Perspective

Artificial Intelligence in Basic and Clinical Neuroscience: Opportunities and Ethical Challenges

The rise of flexible electronics in neuroscience, from materials selection to in vitro and in vivo applications

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