Improved tool to aid brain understanding, one section at a time

In the brain, billions of neurons reach each other, exchange information, store memories, interact with danger, and more. Scientists have barely scratched the surface of the more complex organ, but the new device to automatically collect tissue for analysis could allow a faster and deeper dive into the brain.

Their approach was published in IEEE / CAA Journal of Automatica Sinica, Which is a joint publication between IEEE and China Automation Association.

“The ultimate goal of this study is to further enhance the speed and quality of three-dimensional reconstructions of brain nerve connections,” said author Longqing, professor at the State Key Laboratory for Management and Control of Complex Systems, Institute of Automation, China. Academy of Sciences.

Currently, researchers create thin, sequential slices of brain tissue or animal tissue samples – smaller than the width of a human hair – using a cutting tool called a microtome. The tissue floats in water, from which researchers collect the sections and place them on a silicon wafer to be imaged with an electron microscope. Once the images are captured, they are digitally reconstructed into a 3D model.

“Manual combination of brain sections requires operators to have a very high professional knowledge, and it consumes a great deal of time and energy,” said Cheng. “The natural way to overcome this limitation is to use robotic automation technology to improve group effectiveness.”

Researchers have developed a circular silicon wafer that rotates as part of a microtome. While cutting sections of the brain, the rotational motion moves the water so that the sections automatically stick to the chip. The device, called a robotic silicon layer super-micrometer (ASUM), is controlled by an automated system that detects sections of the brain on the surface of the water to improve assembly efficiency, increasing the number of sections each chip can accommodate.

“The proposed ASUM could reduce assembly skill requirements for the operator, and the interventions that the operator must perform are less demanding than using existing auxiliary devices,” said Cheng. It also guarantees the quality of electron microscopy imaging of parts of the brain without cumbersome post-processing operations.

However, it is not a fully automatic system, as the device cannot automatically replace the silicon chip, Cheng said. Next, the researchers plan to introduce an automatic silicon wafer replacement device that includes an advanced control system.

“Understanding the structure of neural connections in the brain helps to explore the mechanism of action of the human brain, to enhance the diagnosis and treatment of brain diseases and to develop brain-like intelligence systems,” said Cheng. “Our ultimate goal is to test whether the quality and efficiency of the brain’s neural network reconstruction can be improved by the designed autocollector.”


L. Cheng, WZ Liu, C. Zhou, YX Zou, Z.-G. Hou, “Automated silicon-layer microtome for automating array of brain sections in array tomography” IEEE / CAA J. Autom. Seneca, Vol. 8, no. 2, p. 389-401, Feb 2021.

The full text of the paper is available:

http: // www.Igas.Clear /at/Article /Doi /10.1109 /JAS.2021.1003829

IEEE / CAA Journal of Automatica Sinica It aims to spread high-quality, useful and far-reaching research achievements globally, providing an international forum for presenting original ideas and recent findings related to all aspects of automation.

Impact factor I IEEE / CAA Journal of Automatica Sinica It is 5,129, and it ranks among the top 17% (11/63, SCI Q1) in the automation and control systems category, according to the latest journal citation reports released by Clarivate Analytics in 2020. In addition, the latest release of CiteScore is 8.3, and contains Q1 has entered into all three categories to which it belongs (information system, control and systems engineering, artificial intelligence) since 2018.

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