Measuring Consciousness: Causal Density and Integrated Information Event
- Time:
- 16:00 - 17:00
- Date:
- 25 November 2011
- Venue:
- Building 53, Room 4025
Event details
of neural signals that are sensitive to conscious level. Such measures should be high for vivid alert conscious wakefulness, and low for unconscious states such as dreamless sleep, coma, and general anesthesia. I will describe recent progress in the development of measures of dynamical complexity, in particular ‘causal density’ and ‘integrated information’. These and similar measures capture in different ways the extent to which a system's dynamics are simultaneously differentiated and integrated. Because conscious scenes are distinguished by the same dynamical features, these measures are therefore good candidates for reflecting conscious level. After reviewing the theoretical background, I will present some simulation results demonstrating similarities and differences between the measures, as well as recent results and challenges in the practical application of the measures to empirically obtained data.
Dr Anil Seth
Complex Systems Simulation Seminar Series (CS^4)
from the Institute for Complex Systems Simulation , the Complexity in Real-World Contexts USRG , and the Computational Modelling Group .
Speaker
Dr Anil Seth, Co-Director,
Sackler Centre for Consciousness Science
School of Informatics, University of Sussex
Abstract
An outstanding challenge in neuroscience is to develop theoretically grounded and practically applicable quantitative measures of neural signals that are sensitive to conscious level. Such measures should be high for vivid alert conscious wakefulness, and low for unconscious states such as dreamless sleep, coma, and general anesthesia. I will describe recent progress in the development of measures of dynamical complexity, in particular ‘causal density' and ‘integrated information'. These and similar measures capture in different ways the extent to which a system's dynamics are simultaneously differentiated and integrated. Because conscious scenes are distinguished by the same dynamical features, these measures are therefore good candidates for reflecting conscious level. After reviewing the theoretical background, I will present some simulation results demonstrating similarities and differences between the measures, as well as recent results and challenges in the practical application of the measures to empirically obtained data.
Short bio: Anil Seth is currently a Reader in the School of Informatics at the University of Sussex, co-director of the Sackler Centre for Consciousness Science, and an EPSRC Leadership Fellow in computational neuroscience. Research in his group integrates mathematical, theoretical, and experimental approaches to unravelling the neural mechanisms underlying consciousness, in humans and other animals, and in health and in disease. A second and complementary interest lies in statistical approaches to causal inference in complex network dynamics. Anil studied natural sciences at Cambridge, artificial intelligence at Sussex, and spent five years as a Postdoctoral and Associate fellow at The Neurosciences Institute in San Diego before returning to Sussex in 2006.
Refreshments
5.00 pm, lecture starts at 4pm.
Complex Systems Simulation Seminar Series
For the complete CS^4 schedule please click here: http://www.interdisciplinary.soton.ac.uk/cs4.html