Skip to main content
eScholarship
Open Access Publications from the University of California

Simultaneous Coding of Microscopic and Macroscopic Features of Touch in Mouse Somatosensory Cortex

  • Author(s): Isett, Brian Robert
  • Advisor(s): Feldman, Daniel E
  • et al.
Abstract

The cerebral cortex is thought to generate sensory experience and facilitate broadly integrative processing used in attention, decision making, and learning. A major goal in neuroscience is to understand how neurons in cortex interact to represent sensory change in the world. Rodents use whiskers to actively palpate their surroundings and gather tactile information. While it is known that rodents can discriminate different textures using whisker input, how the whisker system encodes local spatial features, like shape, is not well understood.

For many perceptual tasks rodents must pay attention to whisker input in order to extract relevant sensory information. Neural oscillations (gamma) may indicate attentive brain states, and Chapter 2 explores how sensory experience may shape the brain’s ability to generate these rhythms. Superficial layers of primary somatosensory cortex (S1) showed a profound reduction in recurrent inhibition after sensory deprivation, as well as a sharp reduction in spontaneous and evoked gamma oscillations. These findings suggest cortical rhythms change with sensory experience in a recurrent inhibition-dependent manner.

How the whisker system encodes spatial features, like shape is unknown. In Chapter 3 we describe an experiment designed to study basic elements of shape encoding, using a set of tactile gratings. We trained mice to discriminate smooth surfaces from rough surfaces composed of raised gratings or sandpaper. High-speed whisker imaging revealed that stick-slip micromotions clustered on discrete grating ridges, evoking spatially and temporally precise spikes in S1. At the same time, slip-responsive neurons also responded to whisker contact and texture, forming an overlapping population of tactile feature responses. Mean firing rate was higher on rough surfaces due to stick-slip-evoked spikes, and by weighting individual units we could accurately predict rough vs. smooth trials from neural activity alone. Surprisingly, 20% of neurons showed selectivity among rough textures, including tuning for specific gratings. Thus, S1 neurons simultaneously coded microscopic and macroscopic features of touch during active palpation of tactile gratings.

Main Content
Current View