Heterogeneity of synaptic input connectivity regulates spike-based neuronal avalanches

Area of Science:

• Neuroscience
• Computational Neuroscience
• Complex Systems

Background:

• The brain operates near a critical non-equilibrium point, generating self-organized neuronal avalanches.
• Understanding the circuitry mechanisms of these avalanches is a key neuroscience challenge.
• The role of structural heterogeneity in synaptic connectivity on avalanche dynamics is poorly understood.

Purpose of the Study:

• To computationally model and predict the effects of structural heterogeneity on neuronal avalanche dynamics.
• To investigate how input and output connectivity variations influence avalanche generation and characteristics.
• To elucidate the circuitry mechanisms underlying neuronal avalanches in heterogeneous networks.

Main Methods:

• Computational modeling of neural networks with varying degrees of input and output connectivity heterogeneity.
• Analysis of avalanche dynamics, including triggering, scaling, and modulation of neural activity.
• Examination of network properties across different in- and out-degree distributions.

Main Results:

• Neuronal avalanches are triggered by intermediate levels of input heterogeneity, but not by output heterogeneity.
• Input heterogeneity modulates both avalanche dynamics and neuronal oscillations within the criticality region.
• Multi-scale cortical activities co-emerge at criticality, influenced by input heterogeneity.
• Findings are robust across various in- and out-degree distributions.

Conclusions:

• Structural heterogeneity, particularly input connectivity, plays a crucial role in regulating neuronal avalanche dynamics.
• Specific patterns of synaptic heterogeneity are necessary for triggering critical brain dynamics.
• These findings provide mechanistic insights into neural self-organization and suggest testable experimental hypotheses.