Ultrastability, Homeostasis and Neural Assemblies

A few months ago I presented a talk entitled “Reappropriating Ashby’s Ultrastability for the Modelling of Neural Assemblies” at the “Cognition and Consciousness” Retecog Summer School 2012. In the talk I analysed homeostatic models derived from R.W. Ashby’s notion of ultrastability and propose a new model inspired in the ideas of homeokinesis and autopoiesis, where the homeostatic variables are the relations between the components of the system instead of the state of the components themselves. The result is a moving and changing homeostatic area which continuously adapt to the agent’s sensorimotor loop.

I recently obtained new results using just three oscillators as a neural controller of a robot in a phototaxis task, which allows us to watch the homeostatic regulation in 3D. The video shows an agent displaying an auto-regulated preference for two different types of light. This autonomous preference emerges as a result of the coordination of homeostatic regulation and sensorimotor activity.

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About maguilera0

Miguel Aguilera is a Postdoctoral Research Fellow at the IAS Research Center for Life, Mind and Society at the University of the Basque Country. He has been a visiting researcher at the Cognitive Science Program at Indiana University and the Ikegami Lab in the Department of General Systems Studies at the University of Tokyo, and a postdoctoral fellow at the University of the University of Zaragoza and the University of the Balearic Islands. His research focuses on autonomy in biological and social systems from an interdisciplinary perspective, integrating insights from cognitive science, theoretical neuroscience, computational modeling, adaptive behaviour, and complex systems. It combines nonlinear and dynamical models, evolutionary algorithms, and mathematical analysis from dynamical systems, network and information theory, to generate and understand situated and embodied models of agency in the realms of artificial life and evolutionary robotics, computational neuroscience, collective intelligence practices and socio-technical systems.
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