Integrated and scalable molecular brain mapping

Understanding the brain requires integrative knowledge of its cellular-, network-, and system-level architectures. Existing volume imaging techniques have proven the potential to provide such information, but the lack of technology to label large volumes for visualization has limited their utility. Here, we address this challenge by developing technologies -- stochastic electrotransport and SWITCH -- to extend multiplexed labeling methods to larger volumes. Stochastic electrotransport selectively expedites transport of molecular probes into the tissue without damaging it. SWITCH synchronizes the labeling reaction to achieve consistent and uniform labeling. These technologies are demonstrated by successfully visualizing several molecular markers in adult mouse brain tissues, which have been previously infeasible in time and cost. Although our focus is on neuroscience, the concepts and methods described in this thesis are quite general. Stochastic electrotransport will be applicable to any nonlinear transport problems, and SWITCH will be applicable to any problem requiring synchronization of reaction kinetics across long distances..

Department dc:contributor.department

Massachusetts Institute of Technology. Department of Chemical Engineering.

Grantor dc:publisher

Massachusetts Institute of Technology

Year dc:date.issued

2017

Author dc:creator

• Cho, Jae H. (Jae Hun)

Advisor dc:contributor.advisor

• Kwanghun Chung.

• Chemical Engineering.

Statement dc:rights

• MIT theses are protected by copyright. They may be viewed, downloaded, or printed from this source but further reproduction or distribution in any format is prohibited without written permission.

Licence dc:rights.uri

• http://dspace.mit.edu/handle/1721.1/7582

Language dc:language.iso

eng

Handle dc:identifier.uri

http://hdl.handle.net/1721.1/111262

OAI identifier oai:identifier

oai:dspace.mit.edu:1721.1/111262