Reverse engineering of feedforward cortical-Hippocampal microcircuits for modelling neural network function and...

Area of Science:

• Neuroscience
• Bioengineering
• Microfluidics

Background:

• Engineered biological neural networks are crucial for studying neural function and dysfunction.
• Advanced neuroengineering can replicate brain network organization.
• Understanding network dynamics is key to neuroscience research.

Purpose of the Study:

• To reverse engineer multinodal neural networks using primary neurons.
• To investigate the functional activity (segregated and integrated) of these engineered networks.
• To model pathological conditions, such as Alzheimer's disease, within these networks.

Main Methods:

• Utilized a custom-designed multinodal microfluidic device with Tesla valve-inspired microtunnels.
• Interfaced the microfluidic device with nanoporous microelectrodes for neural activity recording.
• Induced localized perturbations with amyloid beta to assess network response to pathology.
• Demonstrated long-term culturing of specific neurons from Alzheimer's model mice and rats.

Main Results:

• Engineered neural networks exhibited both segregated and integrated functional activity, mimicking brain dynamics.
• The model system successfully replicated localized pathological impacts using amyloid beta.
• Achieved long-term culturing of anatomically relevant subregion- and layer-specific neurons.

Conclusions:

• The developed microfluidic system enables the reverse engineering of anatomically relevant multinodal neural networks.
• This approach facilitates the study of dynamic structure-function relationships in both healthy and pathological brain states.
• The model holds significant potential for advancing neuroscience research and understanding neurological disorders.