Linear and categorical coding units in the mouse gustatory cortex drive population dynamics and behavior in taste...

Area of Science:

• Neuroscience
• Computational Neuroscience
• Decision Neuroscience

Background:

• Cortical circuits generate complex neural activity essential for perception and behavior.
• The specific roles of individual neurons in population dynamics and overall behavior are not fully understood.

Purpose of the Study:

• To investigate the functional contributions of single neuron activity to population dynamics and behavior in the mouse gustatory cortex (GC).
• To differentiate between sensory, perceptual, and decisional roles of neurons during a taste-based decision-making task.

Main Methods:

• Utilized high-density electrophysiology in mice performing a taste mixture-based decision-making task.
• Employed computational modeling, specifically a recurrent neural network (RNN) model of the GC.
• Classified single neurons based on their linear and categorical activity patterns.

Main Results:

• GC population activity showed linear representation of stimuli during sampling and categorical representation of choices before decisions.
• Identified distinct neuronal subpopulations encoding sensory, perceptual, and decisional variables.
• Perturbations in the RNN model demonstrated that linear and categorical neurons are vital for normal population dynamics and behavior, while others can be silenced without impact.

Conclusions:

• Linear and categorical coding neurons play essential roles in driving cortical dynamics and behavior during perceptual decision-making.
• These findings offer insights into the functional organization of cortical circuits beyond the gustatory cortex.