Literature DB >> 19379772

A minimally invasive displacement sensor for measuring brain micromotion in 3D with nanometer scale resolution.

Mikko Vähäsöyrinki1, Tuomas Tuukkanen, Hannu Sorvoja, Marko Pudas.   

Abstract

Electrophysiological recordings from a single or population of neurons are currently the standard method for investigating neural mechanisms with high spatio-temporal resolution. It is often difficult or even impossible to obtain stable recordings because of brain movements generated by the cardiac and respiratory functions and/or motor activity. An alternative approach to extensive surgical procedures aimed to reduce these movements would be to develop a control system capable of compensating the relative movement between the recording site and the electrode. As a first step towards such a system, an accurate method capable of measuring brain micromotion, preferably in 3D, in a non-invasive manner is required. A wide variety of technical solutions exist for displacement measurement. However, increased sensitivity in the measurement is often accompanied by strict limitations to sensor handling, implementation and external environment. In addition, majority of the current methods are limited to measurement along only one axis. We present a novel, minimally invasive, 3D displacement sensor with displacement resolution exceeding 70 nm along each axis. The sensor is based on optoelectronic detection of movements of a spring-like element with three degrees of freedom. It is remarkably compact with needle-like probe and can be packaged to withstand considerable mishandling, which allow easy implementation to existing measurement systems. We quantify the sensor performance and demonstrate its capabilities with an in vivo measurement of blowfly brain micromotion in a preparation commonly used for electrophysiology.

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Year:  2009        PMID: 19379772     DOI: 10.1016/j.jneumeth.2009.04.004

Source DB:  PubMed          Journal:  J Neurosci Methods        ISSN: 0165-0270            Impact factor:   2.390


  4 in total

1.  Myogenic contraction of a somatic muscle powers rhythmic flow of hemolymph through Drosophila antennae and generates brain pulsations.

Authors:  Alan R Kay; Daniel F Eberl; Jing W Wang
Journal:  J Exp Biol       Date:  2021-10-22       Impact factor: 3.308

2.  Adaptive movable neural interfaces for monitoring single neurons in the brain.

Authors:  Jit Muthuswamy; Sindhu Anand; Arati Sridharan
Journal:  Front Neurosci       Date:  2011-09-08       Impact factor: 4.677

3.  Compensation of physiological motion enables high-yield whole-cell recording in vivo.

Authors:  William M Stoy; Bo Yang; Ali Kight; Nathaniel C Wright; Peter Y Borden; Garrett B Stanley; Craig R Forest
Journal:  J Neurosci Methods       Date:  2020-11-23       Impact factor: 2.987

4.  3D active stabilization system with sub-micrometer resolution.

Authors:  Olli Kursu; Tuomas Tuukkanen; Timo Rahkonen; Mikko Vähäsöyrinki
Journal:  PLoS One       Date:  2012-08-10       Impact factor: 3.240

  4 in total

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