Biophysical mechanism of the interaction between default mode network and working memory network

Area of Science:

• Computational neuroscience
• Cognitive neuroscience
• Neural networks

Background:

• The default mode network (DMN) is active during rest and linked to higher cognition.
• Interactions between the DMN and task-related networks, like the working memory network (WMN), are not fully understood.
• Working memory involves encoding, maintenance, and retrieval phases.

Purpose of the Study:

• To propose a theoretical model of coupled default mode network (DMN) and working memory network (WMN).
• To investigate the neural mechanisms underlying working memory dynamics and inter-network communication.
• To explore how network parameters influence working memory performance and stability.

Main Methods:

• Developed a computational model of coupled excitatory and inhibitory neurons representing the DMN and WMN.
• Simulated working memory task phases: encoding, maintenance, and retrieval.
• Analyzed network dynamics, oscillations, and functional connectivity using parameters like NMDA conductance and coupling strengths.

Main Results:

• AMPA channels facilitate synchronous oscillations crucial for state transitions.
• NMDA conductance variations generate distinct neural activity modes, enabling switching between working memory phases.
• DMN stabilizes working memory, with energy consumption related to memorized stimuli.
• Functional connectivity and phase synchronization between DMN and WMN vary across working memory phases, aligning with fMRI findings.

Conclusions:

• The coupled interaction between the WMN and DMN is vital for working memory.
• Network parameters and their interactions dictate working memory capacity and stability.
• The model provides insights into neural mechanisms underlying dynamic brain states during cognitive tasks.