Perceptual spaces: mathematical structures to neural mechanisms

Area of Science:

• Neuroscience
• Computational Neuroscience
• Sensory Neuroscience

Background:

• Understanding how neural populations encode environmental percepts is a key neuroscience goal.
• Representations are organized within perceptual spaces, the geometry of which is crucial for information processing.

Purpose of the Study:

• To explore fundamental properties of neural representations and perceptual spaces.
• To investigate how geometric structures of perceptual spaces inform neural coding principles and mechanisms.
• To compare diverse sensory systems' solutions to common neural processing challenges.

Main Methods:

• Experimental determination of geometric structures within perceptual spaces across various sensory domains (color, vision, audition, olfaction, touch).
• Analysis of neural coding principles and mechanisms informed by perceptual space geometry.
• Comparative analysis of neural architectures and their solutions to dimensionality reduction, mapping strategies, and utilization of natural stimuli statistics.

Main Results:

• Geometric structures of perceptual spaces can be experimentally determined.
• These structures provide insights into neural coding principles and the mechanisms generating these codes.
• Diverse sensory systems exhibit varied solutions for dimensionality reduction, mapping, and processing natural stimuli.

Conclusions:

• The geometry of perceptual spaces is fundamental to understanding neural representations of the environment.
• Comparative analysis across sensory systems highlights common challenges and diverse neural solutions in sensory processing.
• Investigating perceptual space geometry offers a unified framework for understanding neural coding across different sensory modalities.