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 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.
Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology, Cambridge, MA 0213, USA.|Univ. Grenoble Alpes, LTM, F-38000 Grenoble, France.|CNRS, LTM, F-38000 Grenoble, France.
Thibault
T
Honegger
Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology, Cambridge, MA 0213, USA.
Moritz I
MI
Thielen
Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology, Cambridge, MA 02139, USA.|Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA.
Soheil
S
Feizi
Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA.|McGovern Institute for Brain Research, Department of Brain and Cognitive Sciences, Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA 02139, USA.
Neville E
NE
Sanjana
Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology, Cambridge, MA 0213, USA.
Joel
J
Voldman
D000818:Animals; D002478:Cells, Cultured; D002490:Central Nervous System / Q000502:physiology; D051379:Mice; D046210:Microfluidic Analytical Techniques / Q000295:instrumentation*; D008954:Models, Biological; D016501:Neurites / Q000502:physiology*; D009474:Neurons / Q000166:cytology*