Propagating waves can explain irregular neural dynamics.

Area of Science:

• Neuroscience
• Computational Neuroscience
• Neural Dynamics

Background:

• Cortical neurons display irregular firing patterns in vivo.
• Existing models propose either balanced excitation-inhibition or synchronized synaptic inputs as causes.
• The underlying network mechanisms for synchronized inputs and irregular dynamics remain unclear.

Purpose of the Study:

• To investigate network mechanisms generating synchronized synaptic inputs.
• To account for irregular neural dynamics using a detailed neural network model.
• To reconcile existing models of neural dynamics.

Main Methods:

• Investigated a spatially extended, conductance-based spiking neural network model.
• Analyzed emergent propagating wave patterns and their dynamics.
• Examined conditions for wave emergence and their impact on neural activity.

Main Results:

• Propagating wave patterns with complex dynamics emerged from the network model.
• These waves delivered synchronized synaptic inputs to neurons.
• Wave patterns required balanced excitation and inhibition, reconciling major models.
• Wave dynamics explained spike timing variability, firing rate fluctuations, and correlated membrane potentials.
• Model predicted non-Gaussian distributions for synaptic conductance and membrane potential, matching experimental data.

Conclusions:

• Propagating waves provide a mechanistic explanation for irregular neural dynamics.
• The study reconciles balanced excitation-inhibition and synchronized input models.
• Neural firing, though irregular at the single-neuron level, can exhibit coherent population-level structures like waves.