How to measure consciousness

I think what constitutes consciousness is making up a narrative about what is ‘selected’.  The evolutionary reason for making up this narrative is to enter it into memory so it can be explained to others and to yourself when you face a similar choice in the future.  That the memory of these past decisions took the form of a narrative derives from the fact that we are a social species, as explained by Julian Jaynes.  This explains why the narrative is sometimes false, and when the part of the brain creating the narrative doesn’t have access to the part deciding, as in some split brain experiments, the narrative is just confabulated.  I find Dennett’s modular brain idea very plausible and it’s consistent with the idea that consciousness is the function of a module that produces a narrative for memory.  If were designing a robot which I intended to be conscious, that’s how I would design it: With a module whose function was to produce a narrative of choices and their supporting reasons for a memory that would be accessed in support of future decisions.  This then requires a certain coherence and consistency in robots decisions – what we call ‘character’ in a person.  I don’t think that would make the robot necessarily conscious according to Bruno Marchal’s critereon of being able to do Lobian logic.  But if it had to function as a social being, it would need a concept of ‘self’ and the ability for self-reflective reasoning.  Then it would be conscious also according to Bruno. Brent

J Neurosci. 2012 May 16;32(20):7082-90.

Connectivity changes underlying spectral EEG changes during propofol-induced loss of consciousness.


Coma Science Group, Cyclotron Research Centre and Neurology Department, University of Liège and Sart Tilman Hospital, 4000 Liège, Belgium.


The mechanisms underlying anesthesia-induced loss of consciousness remain a matter of debate. Recent electrophysiological reports suggest that while initial propofol infusion provokes an increase in fast rhythms (from beta to gamma range), slow activity (from delta to alpha range) rises selectively during loss of consciousness. Dynamic causal modeling was used to investigate the neural mechanisms mediating these changes in spectral power in humans. We analyzed source-reconstructed data from frontal and parietal cortices during normal wakefulness, propofol-induced mild sedation, and loss of consciousness. Bayesian model selection revealed that the best model for explaining spectral changes across the three states involved changes in corticothalamic interactions. Compared with wakefulness, mild sedation was accounted for by an increase in thalamic excitability, which did not further increase during loss of consciousness. In contrast, loss of consciousness per se was accompanied by a decrease in backward corticocortical connectivity from frontal to parietal cortices, while thalamocortical connectivity remained unchanged. These results emphasize the importance of recurrent corticocortical communication in the maintenance of consciousness and suggest a direct effect of propofol on cortical dynamics.


Adv Exp Med Biol. 2011;718:139-47.

Informational theories of consciousness: a review and extension.


Department of Electrical Engineering, Imperial College, London SW7 2BT, UK.


In recent years a number of people have suggested that there is a close link between conscious experience and the differentiation and integration of information in certain areas of the brain. The balance between differentiation and integration is often called information integration, and a number of algorithms for measuring it have been put forward, which can be used to make predictions about consciousness and to understand the relationships between neurons in a network. One of the key problems with the current information integration measures is that they take a lot of computer processing power, which limits their application to networks of around a dozen neurons. There are also more general issues about whether the current algorithms accurately reflect the consciousness associated with a system. This paper addresses these issues by exploring a new automata-based algorithm for the calculation of information integration. To benchmark different approaches we implemented the Balduzzi and Tononi algorithm as a plugin to the SpikeStream neural simulator, and used it to carry out some preliminary comparisons of the liveliness and Φ measures on simple four neuron networks.

Arch Ital Biol. 2010 Sep;148(3):299-322.

Information integration: its relevance to brain function and consciousness.


Department of Psychiatry, University of Wisconsin, Madison, Wisconsin 53719, USA.


A proper understanding of cognitive functions cannot be achieved without an understanding of consciousness, both at the empirical and at the theoretical level. This paper argues that consciousness has to do with a system’s capacity for information integration. In this approach, every causal mechanism capable of choosing among alternatives generates information, and information is integrated to the extent that it is generated by a system above and beyond its parts. The set of integrated informational relationships generated by a complex of mechanisms–its quale–specify both the quantity and the quality of experience. As argued below, depending on the causal structure of a system, information integration can reach a maximum value at a particular spatial and temporal grain size. It is also argued that changes in information integration reflect a system’s ability to match the causal structure of the world, both on the input and the output side. After a brief review suggesting that this approach is consistent with several experimental and clinical observations, the paper concludes with some prospective remarks about the relevance of understanding information integration for analyzing cognitive function, both normal and pathological.

Biol Bull. 2008 Dec;215(3):216-42.

Consciousness as integrated information: a provisional manifesto.


Department of Psychiatry, University of Wisconsin, Madison, Wisconsin, USA.


The integrated information theory (IIT) starts from phenomenology and makes use of thought experiments to claim that consciousness is integrated information. Specifically: (i) the quantity of consciousness corresponds to the amount of integrated information generated by a complex of elements; (ii) the quality of experience is specified by the set of informational relationships generated within that complex. Integrated information (Phi) is defined as the amount of information generated by a complex of elements, above and beyond the information generated by its parts. Qualia space (Q) is a space where each axis represents a possible state of the complex, each point is a probability distribution of its states, and arrows between points represent the informational relationships among its elements generated by causal mechanisms (connections). Together, the set of informational relationships within a complex constitute a shape in Q that completely and univocally specifies a particular experience. Several observations concerning the neural substrate of consciousness fall naturally into place within the IIT framework. Among them are the association of consciousness with certain neural systems rather than with others; the fact that neural processes underlying consciousness can influence or be influenced by neural processes that remain unconscious; the reduction of consciousness during dreamless sleep and generalized seizures; and the distinct role of different cortical architectures in affecting the quality of experience. Equating consciousness with integrated information carries several implications for our view of nature.


About basicrulesoflife

Year 1935. Interests: Contemporary society problems, quality of life, happiness, understanding and changing ourselves - everything based on scientific evidence.
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