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Metastable dynamics of neural circuits and networks
B A W Brinkman, H Yan1, A Maffei
1State Key Laboratory of Electroanalytical Chemistry, Changchun Institute of Applied Chemistry, Chinese Academy of Sciences, Changchun, Jilin 130022, People's Republic of China.
Applied Physics Reviews
|March 14, 2022
Summary
Neural circuits exhibit metastable dynamics, characterized by sequential activation of discrete states. These dynamics are crucial for sensory processing, expectation, and decision-making in brain function.
Area of Science:
- Neuroscience
- Computational Neuroscience
- Statistical Physics
Background:
- Cortical neurons generate complex spiking activity, forming neural network dynamics.
- Neural dynamics manifest in patterns, either spontaneous or stimulus-evoked.
- Focus on dynamics understood as sequences of discrete, transiently occupied 'metastable' states.
Purpose of the Study:
- Review experimental evidence for neural metastable dynamics.
- Present theoretical and computational approaches to studying metastable activity.
- Connect metastable dynamics to sensory and cognitive functions.
Main Methods:
- Theoretical framework using non-equilibrium statistical physics for network dynamics.
- Statistical approaches for extracting metastable state information from neural signals.
- Neural network modeling informed by experimental data to simulate metastable dynamics.
Main Results:
- Metastable dynamics linked to stimulus coding, expectation, and decision-making in rodents.
- Associated with behavioral performance, choice, task difficulty, and attention in primates.
- Transitions between activity states provide neural basis for perception, memory, and decision-making.
Conclusions:
- Metastable neural activity is fundamental to essential cognitive functions.
- Understanding these dynamics advances knowledge of neural circuit function in health and disease.
- Cohesive view linking state transitions to neural underpinnings of perception, memory, and decision-making.
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