» Articles » PMID: 31011432

Long-term Stability of Neural Signals from Microwire Arrays Implanted in Common Marmoset Motor Cortex and Striatum

Overview
Date 2019 Apr 24
PMID 31011432
Citations 6
Authors
Affiliations
Soon will be listed here.
Abstract

Current neuroprosthetics rely on stable, high quality recordings from chronically implanted microelectrode arrays (MEAs) in neural tissue. While chronic electrophysiological recordings and electrode failure modes have been reported from rodent and larger non-human primate (NHP) models, chronic recordings from the marmoset model have not been previously described. The common marmoset is a New World primate that is easier to breed and handle compared to larger NHPs and has a similarly organized brain, making it a potentially useful smaller NHP model for neuroscience studies. This study reports recording stability and signal quality of MEAs chronically implanted in behaving marmosets. Six adult male marmosets, trained for reaching tasks, were implanted with either a 16-channel tungsten microwire array (five animals) or a Pt-Ir floating MEA (one animal) in the hand-arm region of the primary motor cortex (M1) and another MEA in the striatum targeting the nucleus accumbens (NAcc). Signal stability and quality was quantified as a function of array yield (active electrodes that recorded action potentials), neuronal yield (isolated single units during a recording session), and signal-to-noise ratio (SNR). Out of 11 implanted MEAs, nine provided functional recordings for at least three months, with two arrays functional for 10 months. In general, implants had high yield, which remained stable for up to several months. However, mechanical failure attributed to MEA connector was the most common failure mode. In the longest implants, signal degradation occurred, which was characterized by gradual decline in array yield, reduced number of isolated single units, and changes in waveform shape of action potentials. This work demonstrates the feasibility of longterm recordings from MEAs implanted in cortical and deep brain structures in the marmoset model. The ability to chronically record cortical signals for neural prosthetics applications in the common marmoset extends the potential of this model in neural interface research.

Citing Articles

Pro-myelinating clemastine administration improves recording performance of chronically implanted microelectrodes and nearby neuronal health.

Chen K, Cambi F, Kozai T Biomaterials. 2023; 301:122210.

PMID: 37413842 PMC: 10528716. DOI: 10.1016/j.biomaterials.2023.122210.


Activation of inflammasomes and their effects on neuroinflammation at the microelectrode-tissue interface in intracortical implants.

Franklin M, Bennett C, Arboite M, Alvarez-Ciara A, Corrales N, Verdelus J Biomaterials. 2023; 297:122102.

PMID: 37015177 PMC: 10614166. DOI: 10.1016/j.biomaterials.2023.122102.


Intracortical Microelectrode Array Unit Yield under Chronic Conditions: A Comparative Evaluation.

Usoro J, Sturgill B, Musselman K, Capadona J, Pancrazio J Micromachines (Basel). 2021; 12(8).

PMID: 34442594 PMC: 8400387. DOI: 10.3390/mi12080972.


The complement cascade at the Utah microelectrode-tissue interface.

Bennett C, Alvarez-Ciara A, Franklin M, Dietrich W, Prasad A Biomaterials. 2020; 268:120583.

PMID: 33310540 PMC: 7856077. DOI: 10.1016/j.biomaterials.2020.120583.


Toward Standardization of Electrophysiology and Computational Tissue Strain in Rodent Intracortical Microelectrode Models.

Mahajan S, Hermann J, Bedell H, Sharkins J, Chen L, Chen K Front Bioeng Biotechnol. 2020; 8:416.

PMID: 32457888 PMC: 7225268. DOI: 10.3389/fbioe.2020.00416.


References
1.
Prasad A, Sanchez J . Quantifying long-term microelectrode array functionality using chronic in vivo impedance testing. J Neural Eng. 2012; 9(2):026028. DOI: 10.1088/1741-2560/9/2/026028. View

2.
Chestek C, Gilja V, Nuyujukian P, Foster J, Fan J, Kaufman M . Long-term stability of neural prosthetic control signals from silicon cortical arrays in rhesus macaque motor cortex. J Neural Eng. 2011; 8(4):045005. PMC: 3644617. DOI: 10.1088/1741-2560/8/4/045005. View

3.
Aflalo T, Kellis S, Klaes C, Lee B, Shi Y, Pejsa K . Neurophysiology. Decoding motor imagery from the posterior parietal cortex of a tetraplegic human. Science. 2015; 348(6237):906-10. PMC: 4896830. DOI: 10.1126/science.aaa5417. View

4.
Downey J, Weiss J, Muelling K, Venkatraman A, Valois J, Hebert M . Blending of brain-machine interface and vision-guided autonomous robotics improves neuroprosthetic arm performance during grasping. J Neuroeng Rehabil. 2016; 13:28. PMC: 4797113. DOI: 10.1186/s12984-016-0134-9. View

5.
Falcone J, Carroll S, Saxena T, Mandavia D, Clark A, Yarabarla V . Correlation of mRNA Expression and Signal Variability in Chronic Intracortical Electrodes. Front Bioeng Biotechnol. 2018; 6:26. PMC: 5880884. DOI: 10.3389/fbioe.2018.00026. View