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哺乳动物的大脑皮层是如何连接的?(How Is the Cerebral Cor

2022-07-07 01:59 作者:LuckyJackie  | 我要投稿

Timeline


00:01


What Is Your Research Question?

你的科研问题是什么?

Try to find rules by which nerves are wired up in the cerebral cortex (outermost layer).


02:08


Which Method Did You Employ?

你运用了哪些方法?

  1. image data with electron microscopes.
  2. extract nerve cell network by machine learning and human annotators.d


05:15


What Are Your Findings?

你的发现是什么?

In the medial entorhinal cortex, axons and their synapses are embedded in a triad circuit motif with cellular feed-forward inhibition.


07:30


What Is the Relevance of Your Findings?

有哪些内容有关于你的发现?

  1. highly precise networks, which challenge old assumptions.
  2. circuit motifs.
  3. synchronous activity.


10:30


Your Outlook for the Future?

你对于未来的展望?

  1. Some circuit motifs are already found in rats. What about apes and humans?
  2. How do you combine context with sensory input in algorithms?
  3. Could alteration of the rules of human circuits lead to disease?

Publication

  1. Helene Schmidt, Anjali Gour, Jakob Straehle, Kevin M. Boergens, Michael Brecht and Moritz Helmstaedter. "Axonal Synapse Sorting in Medial Entorhinal Cortex." Nature 549 (2017): 469-475.
  2. Kevin M. Boergens, Manuel Berning, Tom Bocklisch, Dominic Bräunlein, Florian Drawitsch, Johannes Frohnhofen, Tom Herold, Philipp Otto, Norman Rzepka, D. W. Werkmeister, G. Wiese, H. Wissler and Moritz Helmstaedter. "webKnossos: Efficient Online 3D Data Annotation for Connectomics." Nature Methods 14, 7 (2017): 691-694.
  3. Benedikt Staffler, Manuel Berning, Kevin M. Boergens, Anjali Gour, Patrick van der Smagt and Moritz Helmstaedter. "SynEM, Automated Synapse Detection for Connectomics." eLife 6 (2017).

Researcher

Moritz Helmstaedter is Director at the Max Planck Institute for Brain Research. Before this appointment, he was the Research Group Leader and Principal Investigator at the Max Planck Institute of Neurobiology. His research field is connectomics, the mapping of neuronal circuits using electron microscopy and machine learning.


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