Slow oscillating population activity in developing cortical networks: models and experimental results

Area of Science:

• Neuroscience
• Computational Neuroscience
• Developmental Neuroscience

Background:

• Developing neuronal networks exhibit synchronized oscillatory activity.
• Multiple mechanisms can drive this early network activity, each with unique consequences.
• Understanding these mechanisms is crucial for comprehending network formation and function.

Purpose of the Study:

• To investigate the emergence of oscillatory activity in developing cortical networks.
• To compare computational models with in vitro experimental recordings.
• To elucidate the distinct roles of different neuronal firing patterns and synaptic mechanisms.

Main Methods:

• Utilized three computational models of leaky integrate-and-fire neurons with adaptation and depressing synapses.
• Simulated networks driven by intrinsically bursting, intrinsically random spiking, or spontaneous synaptic activity.
• Performed multisite extracellular recordings from developing cortical networks in vitro.

Main Results:

• Model networks driven by intrinsically bursting neurons closely matched the activity of 1-week-old cortical cultures.
• Intrinsically bursting neurons were found in cultures younger than 3 weeks in vitro.
• Synaptically dependent random spiking increased in cultures older than 3 weeks in vitro.
• Distributed stimulation was more effective in suppressing population bursts than focal stimulation.

Conclusions:

• Intrinsically bursting neurons effectively model early emergent recurrent population activity in young networks.
• Spontaneous synaptic activity better explains the activity patterns in more mature networks.
• Distributed stimulation's efficacy in burst suppression is attributed to broader synaptic depression.