Microfluidic neurite guidance to study structure-function relationships in topologically-complex population-based neural networks
The central nervous system is a dense, layered, 3D interconnected network of populations of neurons, and thus recapitulating that complexity for in vitro CNS models requires methods that can create defined topologically-complex neuronal networks. Several three-dimensional patterning approaches have...
| Main Authors: | , , , , |
|---|---|
| Other Authors: | |
| Format: | Article |
| Language: | en_US |
| Published: |
Nature Publishing Group
2017
|
| Online Access: | http://hdl.handle.net/1721.1/109255 https://orcid.org/0000-0001-8898-2296 https://orcid.org/0000-0002-0964-0616 |
| _version_ | 1811075007591219200 |
|---|---|
| author | Honegger, Thibault Thielen, Moritz Imanuel Voldman, Joel Feizi- Khankandi, Soheil Sanjana, Neville E |
| author2 | Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory |
| author_facet | Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory Honegger, Thibault Thielen, Moritz Imanuel Voldman, Joel Feizi- Khankandi, Soheil Sanjana, Neville E |
| author_sort | Honegger, Thibault |
| collection | MIT |
| description | The central nervous system is a dense, layered, 3D interconnected network of populations of neurons, and thus recapitulating that complexity for in vitro CNS models requires methods that can create defined topologically-complex neuronal networks. Several three-dimensional patterning approaches have been developed but none have demonstrated the ability to control the connections between populations of neurons. Here we report a method using AC electrokinetic forces that can guide, accelerate, slow down and push up neurites in un-modified collagen scaffolds. We present a means to create in vitro neural networks of arbitrary complexity by using such forces to create 3D intersections of primary neuronal populations that are plated in a 2D plane. We report for the first time in vitro basic brain motifs that have been previously observed in vivo and show that their functional network is highly decorrelated to their structure. This platform can provide building blocks to reproduce in vitro the complexity of neural circuits and provide a minimalistic environment to study the structure-function relationship of the brain circuitry. |
| first_indexed | 2024-09-23T09:58:53Z |
| format | Article |
| id | mit-1721.1/109255 |
| institution | Massachusetts Institute of Technology |
| language | en_US |
| last_indexed | 2024-09-23T09:58:53Z |
| publishDate | 2017 |
| publisher | Nature Publishing Group |
| record_format | dspace |
| spelling | mit-1721.1/1092552022-09-30T18:08:39Z Microfluidic neurite guidance to study structure-function relationships in topologically-complex population-based neural networks Honegger, Thibault Thielen, Moritz Imanuel Voldman, Joel Feizi- Khankandi, Soheil Sanjana, Neville E Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science McGovern Institute for Brain Research at MIT Honegger, Thibault Thielen, Moritz Imanuel Voldman, Joel Feizi- Khankandi, Soheil Sanjana, Neville E The central nervous system is a dense, layered, 3D interconnected network of populations of neurons, and thus recapitulating that complexity for in vitro CNS models requires methods that can create defined topologically-complex neuronal networks. Several three-dimensional patterning approaches have been developed but none have demonstrated the ability to control the connections between populations of neurons. Here we report a method using AC electrokinetic forces that can guide, accelerate, slow down and push up neurites in un-modified collagen scaffolds. We present a means to create in vitro neural networks of arbitrary complexity by using such forces to create 3D intersections of primary neuronal populations that are plated in a 2D plane. We report for the first time in vitro basic brain motifs that have been previously observed in vivo and show that their functional network is highly decorrelated to their structure. This platform can provide building blocks to reproduce in vitro the complexity of neural circuits and provide a minimalistic environment to study the structure-function relationship of the brain circuitry. 2017-05-22T16:15:35Z 2017-05-22T16:15:35Z 2016-06 2016-01 Article http://purl.org/eprint/type/JournalArticle 2045-2322 http://hdl.handle.net/1721.1/109255 Honegger, Thibault et al. “Microfluidic Neurite Guidance to Study Structure-Function Relationships in Topologically-Complex Population-Based Neural Networks.” Scientific Reports 6.1 (2016): n. pag. © 2017 Macmillan Publishers Limited, https://orcid.org/0000-0001-8898-2296 https://orcid.org/0000-0002-0964-0616 en_US http://dx.doi.org/10.1038/srep28384 Scientific Reports Creative Commons Attribution 4.0 International License http://creativecommons.org/licenses/by/4.0/ application/pdf Nature Publishing Group Nature |
| spellingShingle | Honegger, Thibault Thielen, Moritz Imanuel Voldman, Joel Feizi- Khankandi, Soheil Sanjana, Neville E Microfluidic neurite guidance to study structure-function relationships in topologically-complex population-based neural networks |
| title | Microfluidic neurite guidance to study structure-function relationships in topologically-complex population-based neural networks |
| title_full | Microfluidic neurite guidance to study structure-function relationships in topologically-complex population-based neural networks |
| title_fullStr | Microfluidic neurite guidance to study structure-function relationships in topologically-complex population-based neural networks |
| title_full_unstemmed | Microfluidic neurite guidance to study structure-function relationships in topologically-complex population-based neural networks |
| title_short | Microfluidic neurite guidance to study structure-function relationships in topologically-complex population-based neural networks |
| title_sort | microfluidic neurite guidance to study structure function relationships in topologically complex population based neural networks |
| url | http://hdl.handle.net/1721.1/109255 https://orcid.org/0000-0001-8898-2296 https://orcid.org/0000-0002-0964-0616 |
| work_keys_str_mv | AT honeggerthibault microfluidicneuriteguidancetostudystructurefunctionrelationshipsintopologicallycomplexpopulationbasedneuralnetworks AT thielenmoritzimanuel microfluidicneuriteguidancetostudystructurefunctionrelationshipsintopologicallycomplexpopulationbasedneuralnetworks AT voldmanjoel microfluidicneuriteguidancetostudystructurefunctionrelationshipsintopologicallycomplexpopulationbasedneuralnetworks AT feizikhankandisoheil microfluidicneuriteguidancetostudystructurefunctionrelationshipsintopologicallycomplexpopulationbasedneuralnetworks AT sanjananevillee microfluidicneuriteguidancetostudystructurefunctionrelationshipsintopologicallycomplexpopulationbasedneuralnetworks |