![]() Some examples of neural prostheses include cochlear implants that can aid in restoring hearing, artificial silicon retina microchips that have shown to be effective in treating retinal degeneration from retinitis pigmentosa, and even motor prostheses that could offer the capability for movement in those affected with quadriplegia or disorders like amyotrophic lateral sclerosis. Clinical and health applications Neural prosthetics In one proposed model of the neural dust sensor, the transistor model allowed for a method of separating between local field potentials and action potential "spikes", which would allow for a greatly diversified wealth of data acquirable from the recordings. The piezoelectric crystal detects the neuronal signal from its location in the extracellular space, and the ultrasound energy reflected back to the interrogator would be modulated in a way that would communicate the recorded activity. Neural dust employs this method by having the sub-dural communicator send out an ultrasound pulse that is then reflected by the neural dust sensors. As they reflect the RF energy back to the interrogator, they are capable of modulating the frequency, and in doing so, encoding information. In RFID passive, battery-less tags are capable of absorbing and reflecting radio frequency (RF) energy when in close proximity to a RF interrogator, which is a device that transmits RF energy. Thus backscatter communication, adopted from radio frequency identification (RFID) technologies, is employed. Use of ultrasound also permits greater scaling of sensor nodes, allowing for sizes less than 100 µm, which provides great possibility in the realm of implantable electronics.ĭue to the extremely small size of the neural dust motes, it would be impractical and nearly impossible to create a functional transmitter in the sensor itself. This excess energy would take the form of heat, which would cause damage to the surrounding tissue. ![]() This results in higher penetration depths (and therefore easier communication with the sub-cranial communicator), as well as reduced unwanted energy being distributed into the body's tissues due to scattering or absorption. While many comparable devices use electromagnetic waves (such as radio frequencies) to interact with wireless neural sensors, use of ultrasound offers the advantages of higher spatial resolution as well as decreased attenuation in the tissue. ![]() While many forms of BCI exist, neural dust is in a class of its own due to its size, wireless capability, and use of ultrasound technology. The piezoelectric crystal is capable of recording brain activity from the extracellular space, and converting it into an electrical signal. The neural dust motes consist of a pair of recording electrodes, a custom transistor, and a piezoelectric sensor. The principal components of the neural dust system include the sensor nodes (neural dust), which aim to be in the 10-100 µm 3 scale, and a sub-cranial interrogator, which would sit below the dura mater and would provide both power and a communication link to the neural dust. While the terms can sometimes be used interchangeably, the main difference is that while BCI generally interface neural activity directly to a computer, neuroprosthetics tend to connect activity in the central nervous system to a device meant to replace the function of a missing or impaired body part. While neural dust does fall under the category of BCI, it also could be used in the field of neuroprosthetics (also known as neural prosthetics). The hallmark research of the field came from the University of California, Los Angeles (UCLA), following a research grant from the National Science Foundation. While the history of BCI begins with the invention of the electroencephalogram by Hans Berger in 1924, the term did not appear in scientific literature until the 1970s. The design for neural dust was first proposed in a 2011 paper from the University of California, Berkeley Wireless Research Center, that described both the challenges and outstanding benefits of creating a long lasting wireless brain computer interface (BCI). The term is derived from " smart dust", as the sensors used as neural dust may also be defined by this concept. In practice, a medical treatment could introduce thousands of neural dust devices into human brains. The sensors may be used to study, monitor, or control the nerves and muscles and to remotely monitor neural activity. Neural dust is a term used to refer to nanometer-sized devices operated as wirelessly powered nerve sensors it is a type of brain–computer interface. Nerve sensors used in brain-computer interfaces
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