Cortical network dynamics with time delays reveals functional connectivity in the resting brain

Area of Science:

• Neuroscience
• Computational Neuroscience
• Systems Neuroscience

Background:

• Spontaneous, temporally coherent fluctuations in cortical regions like the prefrontal and cingulate cortices characterize the brain's resting state.
• The origin of these resting-state fluctuations remains unclear, with stochastic processes being a leading hypothesis.

Purpose of the Study:

• To investigate the role of time delays in neural network dynamics for generating resting-state fluctuations.
• To test the hypothesis that time delays are crucial for the emergence of characteristic resting-state networks.

Main Methods:

• A computational network model based on primate cortical connectivity was utilized.
• Time delays within the network were systematically scaled by adjusting signal propagation velocity.
• Biophysically realistic parameters were employed to simulate network dynamics.

Main Results:

• The study demonstrated the emergence of resting-state networks by tuning time delays.
• Scaling time delays led to the generation of temporally coherent fluctuations characteristic of resting states.
• These findings were observed under biophysically realistic parameter conditions.

Conclusions:

• Time delays in neural network dynamics are a critical factor in generating spontaneous resting-state fluctuations.
• The results support the hypothesis that network timing, rather than purely stochastic processes, can explain the origin of resting-state networks.
• This work provides a mechanistic explanation for the emergence of intrinsic brain activity patterns.