Microsystem Technologies

, Volume 23, Issue 8, pp 3671–3683 | Cite as

Sustained elevation of activity of developing neurons grown on polyimide microelectrode arrays (MEA) in response to ultrasound exposure

  • Massoud L. Khraiche
  • William B. Phillips
  • Nathan Jackson
  • Jit Muthuswamy
Technical Paper


High frequency ultrasound (HFUS) is an attractive modality for noninvasive clinical applications such as imaging, diagnostics and more recently for stimulation of the central nervous system. The aim of this study was to investigate the modulation in the electrical activity of developing neurons due to the application of HFUS using polyimide based microelectrode array (MEA) that is acoustically transparent in order to allow ultrasound waves to transmit through the substrate and reach the growing neural layer. High frequency tone bursts of ultrasound were applied to a monolayer of developing primary neurons grown on an acoustical transparent polyimide MEA. HFUS was applied to primary neuronal culture at two frequencies (4.4 and 96 MHz) with spatial peak-temporal average intensities of 100 and 10 mW/cm2. Exposures were found to increase the spike rate of neurons in culture up to 20-fold in some cases and induce silent or still developing neurons to fire at a maximum rate of up to three new units per recording microelectrode. Another new observation reported in this study is that the increase in spike rate was sustained for over 6 min post stimulation. Our results also suggest that mechanical and not thermal effects of ultrasound largely mediate the increase in electrical excitability without any discernible spatial pattern or preference across the monolayer for the US parameters used in this study. The accessibility of the disassociated neuronal cultures to stimulation, imaging and recording provides a useful model for investigating the exact mechanisms behind the effect of ultrasound on neuronal excitability.


Polyimide Spike Rate Ultrasound Wave Pressure Pattern Microelectrode Array 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.



The authors would like to thank Dr. Bruce Towe, Professor of Biomedical Engineering at Arizona State University for his helpful discussions and insights.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2016

Authors and Affiliations

  • Massoud L. Khraiche
    • 1
    • 2
  • William B. Phillips
    • 1
  • Nathan Jackson
    • 1
    • 3
  • Jit Muthuswamy
    • 1
  1. 1.Harrington Department of Bioengineering ECG 334Arizona State UniversityTempeUSA
  2. 2.Department of OphthalmologyUniversity of California San DiegoLa JollaUSA
  3. 3.Tyndall National InstituteUniversity College CorkCorkIreland

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