Modeling the Emergence of Circuit Organization and Function during Development.

Area of Science:

• Neuroscience
• Computational Biology
• Developmental Neuroscience

Background:

• Developing neural circuits exhibit unique spontaneous activity patterns and connectivity.
• Activity-dependent plasticity mechanisms shape neural network formation.
• Theoretical and computational models are crucial for understanding spontaneous activity and circuit development.

Purpose of the Study:

• To review recent modeling efforts on spontaneous activity generation in the developing cortex and hippocampus.
• To explore how plasticity mechanisms utilize spontaneous activity for circuit formation and refinement.
• To identify open challenges in linking developmental circuit changes to mature information processing.

Main Methods:

• Review of theoretical and computational modeling studies.
• Focus on models explaining developmental changes in spontaneous activity.
• Analysis of models linking spontaneous activity to plasticity-driven circuit formation.

Main Results:

• Models highlight specific connectivity profiles and strengthening inhibition as drivers of developmental changes in spontaneous activity.
• Computational models mechanistically explore how plasticity uses spontaneous activity to form receptive fields, sensory maps, and recurrent architectures.
• Models provide insights into the gradual refinement of neural circuit connectivity.

Conclusions:

• Spontaneous activity and plasticity are key to neural circuit development.
• Modeling approaches offer a framework for understanding the transition from immature to mature information processing.
• Further research is needed to address functional implications and bridge developmental gaps.