Model validation of untethered, ultrasonic neural dust motes for cortical recording

Seo, Dongjin; Carmena, Jose M.; Rabaey, Jan M.; Maharbiz, Michel M.; Alon, Elad

doi:10.1016/j.jneumeth.2014.07.025

Cited by 146 publications

(100 citation statements)

References 25 publications

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“…Some of the most recent developments will ultimately make intracranial monitoring of FPs a non-invasive approach (Seo et al, 2015), and a further boost for the use of FPs may just be around the corner. Unfortunately, equipment does not come with manuals as to how to interpret brain signals.…”

Section: The Many Faces Of Field Potentialsmentioning

confidence: 99%

Local Field Potentials: Myths and Misunderstandings

Herreras

2016

Front. Neural Circuits

252

244

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The intracerebral local field potential (LFP) is a measure of brain activity that reflects the highly dynamic flow of information across neural networks. This is a composite signal that receives contributions from multiple neural sources, yet interpreting its nature and significance may be hindered by several confounding factors and technical limitations. By and large, the main factor defining the amplitude of LFPs is the geometry of the current sources, over and above the degree of synchronization or the properties of the media. As such, similar levels of activity may result in potentials that differ in several orders of magnitude in different populations. The geometry of these sources has been experimentally inaccessible until intracerebral high density recordings enabled the co-activating sources to be revealed. Without this information, it has proven difficult to interpret a century's worth of recordings that used temporal cues alone, such as event or spike related potentials and frequency bands. Meanwhile, a collection of biophysically ill-founded concepts have been considered legitimate, which can now be corrected in the light of recent advances. The relationship of LFPs to their sources is often counterintuitive. For instance, most LFP activity is not local but remote, it may be larger further from rather than close to the source, the polarity does not define its excitatory or inhibitory nature, and the amplitude may increase when source's activity is reduced. As technological developments foster the use of LFPs, the time is now ripe to raise awareness of the need to take into account spatial aspects of these signals and of the errors derived from neglecting to do so.

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Section: The Many Faces Of Field Potentialsmentioning

confidence: 99%

Local Field Potentials: Myths and Misunderstandings

Herreras

2016

Front. Neural Circuits

252

244

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show abstract

“…Note “tether” here means the interconnect between the device that is in the brain tissue and the connector that is usually mounted on the skull. This may be accomplished by implanting the entire device below the meninges [84], and using ultrasonic [85, 86] or induction [87] based power supplies for signal and/or power communication. While currently limited in ability to gather and transmit high quality information, the potential benefits of wireless devices are tremendous.…”

Section: Strategiesmentioning

confidence: 99%

Recent advances in neural electrode–tissue interfaces

Woeppel

Yang

Cui

2017

Current Opinion in Biomedical Engineering

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Neurotechnology is facing an exponential growth in the recent decades. Neural electrode-tissue interface research has been well recognized as an instrumental component of neurotechnology development. While satisfactory long-term performance was demonstrated in some applications, such as cochlear implants and deep brain stimulators, more advanced neural electrode devices requiring higher resolution for single unit recording or microstimulation still face significant challenges in reliability and longevity. In this article, we review the most recent findings that contribute to our current understanding of the sources of poor reliability and longevity in neural recording or stimulation, including the material failure, biological tissue response and the interplay between the two. The newly developed characterization tools are introduced from electrophysiology models, molecular and biochemical analysis, material characterization to live imaging. The effective strategies that have been applied to improve the interface are also highlighted. Finally, we discuss the challenges and opportunities in improving the interface and achieving seamless integration between the implanted electrodes and neural tissue both anatomically and functionally.

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“…They are also commonly used for human experiments such as prosthetics and Brain Computer Interface (BCI). The miniature brain implants are the new generation of devices under research [6] [7]. They are small enough to float within the deep brain to record neural activity and transmit the data wirelessly to the receiver outside of the brain.…”

Section: A Compression In Wired Data Transmissionmentioning

confidence: 99%

“…The trend of high density electrode integration is expected to continue as researchers are currently designing silicon probes that contains >1000 channels [5]. The researchers are also exploring the possibility of designing a distributed network of sub-100µm recording devices that can float in the brain to record and stimulate the brain tissue [6] [7].…”

Section: Introductionmentioning

confidence: 99%

Communication Channel Analysis and Real Time Compressed Sensing for High Density Neural Recording Devices

Zhang

Duncan

Suo

et al. 2016

IEEE Trans. Circuits Syst. I

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Abstract-Next generation neural recording and BrainMachine Interface (BMI) devices call for high density or distributed systems with more than 1000 recording sites. As the recording site density grows, the device generates data on the scale of several hundred megabits per second (Mbps). Transmitting such large amounts of data induces significant power consumption and heat dissipation for the implanted electronics. Facing these constraints, efficient on-chip compression techniques become essential to the reduction of implanted systems power consumption. This paper analyzes the communication channel constraints for high density neural recording devices. This paper then quantifies the improvement on communication channel using efficient on-chip compression methods. Finally, This paper describes a Compressed Sensing (CS) based system that can reduce the data rate by > 10× times while using power on the order of a few hundred nW per recording channel.

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Model validation of untethered, ultrasonic neural dust motes for cortical recording

Cited by 146 publications

References 25 publications

Local Field Potentials: Myths and Misunderstandings

Local Field Potentials: Myths and Misunderstandings

Recent advances in neural electrode–tissue interfaces

Communication Channel Analysis and Real Time Compressed Sensing for High Density Neural Recording Devices

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