Exogenous control of octopus skin coloration ex vivo
Abstract
The octopus contains a centralized brain, but approximately two-thirds of its ~500 million neurons are in the peripheral nervous system, residing mainly in the nerve cords of the octopus’s eight arms. The nascent field of morphological computing and embodied primitive cognition needs to be brought to bear to understand the contributions of control signals (centralized and locally-generated) as well as materials properties that facilitate adaptive behavior. We will survey the recent scientific literature to determine what is known and what is not known about how the animal initiates various signals (i.e., changing its shape/texture or color/pattern) from the brain to distal regions of the animal (i.e., the skin, the arms, etc.). We will also determine what is already known about the signals that come back up from the skin and the arms to the brain, and then ascertain whether it is possible to intercept these ‘command’ signals and alter them in a predicable manner. A main goal of this phase of the project is to understand the key insights and open questions about how the animal uses this information to determine what to ‘display’ to potential predators/what shape and color it needs to become. At the same time, we will research existing knowledge from other species with similar capabilities that could shed light on the most expeditious way to mimic these capabilities in human technology. Specifically, we will: 1. Construct a custom-built device to monitor and record changes in the color and overall pattern of in vitro or cultured O. vulgaris skin tissue in response to electrical/optical stimuli. 2. Perform cycles of a) stimulation/manipulation of the skin tissue and b) computational analysis of the generated data (using machine-learning algorithms) to ‘decode’ how the octopus skin responds to the applied stimuli ex vivo. By making and testing predictions, it should be possible to further refine and optimize the machine-learning algorithm for use in future in vivo applications.
Document Details
- Document Type
- DoD Grant Award
- Publication Date
- Jul 26, 2018
- Source ID
- N000141812631
Entities
People
- Michael Levin
Organizations
- Office of Naval Research
- Tufts University
- United States Navy