Discrete neocortical dynamics predict behavioral categorization of sounds.

Area of Science:

• Neuroscience
• Computational Neuroscience
• Auditory Perception

Background:

• Perceptual categorization is vital for environmental interaction.
• Discrete brain network dynamics are hypothesized to underlie category formation.
• Previous studies observed such dynamics but lacked direct links to perceptual categories.

Purpose of the Study:

• To investigate if discrete neural dynamics in the auditory cortex correspond to perceptual sound categories.
• To determine if local network activity predicts behavioral categorization performance.
• To establish the role of nonlinear dynamics in spontaneous category generation.

Main Methods:

• In vivo two-photon calcium imaging in the auditory cortex of mice.
• Analysis of local network activity patterns evoked by auditory stimuli.
• Correlation of neural response modes with behavioral discrimination and categorization tasks.

Main Results:

• Auditory cortex activity was constrained to a limited number of distinct response modes.
• Transitions between these modes were abrupt, suggesting attractor-like dynamics.
• Local cortical responses quantitatively predicted mice's ability to discriminate and spontaneously categorize sounds.

Conclusions:

• Local nonlinear dynamics in the auditory cortex generate spontaneous sound categories.
• These neural dynamics provide a mechanism for perceptual categorization.
• The findings link neural dynamics directly to behavioral decisions in auditory perception.