Nelson Lab

Black Ghost Knifefish (Apteronotus albifrons)The Nelson Lab's research is focused on active sensory acquisition. We seek to understand neural mechanisms and computational principles that animals use to actively acquire sensory information in complex, dynamic environments. We are interested in systems-level integration and interactions of:

  • neural coding and spike train statistics
  • sensory signal detection and estimation
  • active repositioning of sensor arrays
  • multiresolution adaptive filtering
  • processing of clustered sensory signals
  • generation and subtraction of sensory expectation

We study these processes in the electrosensory system of weakly electric fish, using a combination of behavioral, electrophysiological, and computational neuroscience approaches.

Our Principal Investigator is Mark E. Nelson.

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Research Focus

Studies of neural information processing in general, and sensory acquisition in particular, are best carried out under conditions that closely approximate the animal's natural environment. Each species has evolved solutions that are adapted to its own behavioral needs and ecological niche. Within this context, we can ask meaningful questions about how the nervous system acquires and processes sensory information. The neural mechanisms and information processing principles that emerge from a careful neuroethological study can have implications beyond the particular system in which they are elucidated. While focusing on the neural and behavioral strategies used by weakly electric fish to detect and capture prey, our goal is to contribute toward a broader understanding of general principles of sensory acquisition. Specific areas of interest include optimal positioning of receptor structures, efficient neural coding, task-specific adaptive filtering, and the generation and subtraction of sensory expectation. Many of the details will, of course, be specific to the electrosensory system, but the general principles that emerge should be broadly applicable to many other systems. Ultimately, we hope to come away with a deeper appreciation of how animals achieve their remarkable information processing capabilities.