Increased Perceptual Reliability Reduces Membrane Potential Variability in Cortical Neurons

Area of Science:

• Neuroscience
• Computational Neuroscience
• Decision Making

Background:

• Uncertainty is a key factor in decision-making across species.
• The neural representation of uncertainty in the cortex is not well understood.
• Theoretical models predict reduced neuronal membrane potential variability with stimulus-triggered uncertainty computation.

Purpose of the Study:

• To investigate how cortical neurons represent and respond to stimulus reliability and uncertainty.
• To test theoretical predictions of reduced membrane potential variability in vivo.
• To explore the role of posterior parietal cortex neurons in multisensory decision-making.

Main Methods:

• Utilized simulation-based inference to analyze membrane potential statistics from single-unit recordings.
• Recorded from posterior parietal cortex neurons in male mice performing a multisensory change detection task.
• Examined the relationship between stimulus reliability and neuronal membrane potential variability.

Main Results:

• Inferred membrane potential statistics revealed a decrease in variability in response to task-relevant stimuli.
• More reliable stimuli induced larger decreases in membrane potential variability compared to less reliable stimuli.
• Findings align with theoretical predictions of uncertainty tracking in cortical neurons.

Conclusions:

• Cortical neurons dynamically adjust their membrane potential variability to track uncertainty.
• This mechanism provides Bayesian benefits for downstream neural computations.
• The study offers insights into the neural basis of decision-making under uncertainty.