In vitro validation of in silico identified inhibitory interactions

Area of Science:

• Neuroscience
• Computational Neuroscience
• Systems Neuroscience

Background:

• Understanding neuronal signal propagation is crucial for deciphering information processing in neural networks.
• Multi-electrode arrays (MEAs) record spike trains to study neural network function.
• Identifying inhibitory connections is challenging due to difficulty distinguishing low firing rates from active inhibition.

Purpose of the Study:

• To develop a method for accurately identifying inhibitory neuronal connections.
• To predict the effects of stimulating or inhibiting single neurons on others.
• To validate computational predictions with experimental data.

Main Methods:

• An in silico interventional procedure was developed to predict neuronal responses to perturbations.
• A Neural Circuit Probe (NCP) was engineered for transient and reversible drug delivery to individual neurons.
• In vitro experiments used the NCP to validate in silico predictions of inhibitory effects.

Main Results:

• The in silico procedure successfully predicted the effects of neuronal interventions.
• The Neural Circuit Probe (NCP) enabled experimental validation of predicted inhibitory connections.
• Putative inhibitory connections identified computationally were confirmed through in vitro experiments.

Conclusions:

• Detailed microcircuitry can be inferred from statistical models derived from neurophysiology data.
• The combined in silico and experimental approach accurately identifies inhibitory neuronal effects.
• This methodology advances the study of neural network dynamics and information processing.