Modeling of spontaneous activity in developing spinal cord using activity-dependent depression in an excitatory...

Area of Science:

• Neuroscience
• Computational Neuroscience
• Developmental Neuroscience

Background:

• Spontaneous episodic activity is characteristic of developing neural networks.
• In embryonic chick spinal cords, this activity involves rhythmic discharges recurring at specific intervals.
• This activity is generated by excitatory connections, not specialized neurons.

Purpose of the Study:

• To develop a qualitative model of a homogeneous, excitatory recurrent network.
• To explain the multiple time-scale spontaneous activity observed in the embryonic chick spinal cord.
• To investigate the roles of synaptic depression and network depression in generating network activity.

Main Methods:

• Developed an idealized, qualitative computational model.
• Simulated network activity based on excitatory connectivity and synaptic depression.
• Modeled slow activity-dependent network depression as cellular excitability modulation or synaptic depression.

Main Results:

• The model demonstrated that fast synaptic depression contributes to rhythmic cycling.
• Slow activity-dependent network depression explains the episodic nature of the activity.
• A model incorporating slow synaptic depression better matched experimental data during excitatory synapse blockade.

Conclusions:

• Excitatory recurrent networks with synaptic depression can generate spontaneous episodic activity.
• Both fast and slow synaptic depression play crucial roles in shaping network dynamics.
• Slow synaptic depression provides a more accurate account of observed network behaviors in the embryonic chick spinal cord.