Information content in cortical spike trains during brain state transitions

Area of Science:

• Neuroscience
• Computational Neuroscience
• Systems Neuroscience

Background:

• The cerebral cortex exhibits continuous spontaneous activity due to recurrent neural connections.
• Understanding how this ongoing activity relates to brain states is crucial for deciphering neural computation.

Purpose of the Study:

• To investigate how the information content of neuronal firing varies with different brain states.
• To quantify changes in information content during transitions between awake and sleep states.

Main Methods:

• Recorded spontaneous neuronal activity (spike trains) and electroencephalogram (EEG) from the primary visual cortex of rats.
• Analyzed information content using Lempel-Ziv Complexity to estimate neural discharge entropy.
• Determined brain state through behavioral evaluation, EEG, and electromyogram (EMG) analysis.

Main Results:

• Information content in spike trains ranged from 4-70 bits/s.
• Transitions to deeper sleep states correlated with a ~30% decrease in information content.
• Transitions to awake states showed a ~30% increase in information content.
• High temporal correlation between neurons indicated a significant impact of brain state on information.

Conclusions:

• Brain state profoundly influences the information processing capacity of individual neurons.
• Spontaneous cortical activity is dynamically modulated by brain state, affecting information transmission.
• These findings highlight the importance of considering brain state in the analysis of neural coding.