Information integration is a measure, developed by Tononi and co-researchers, of the capacity for dynamic neural networks to be in informational states which are unique and indivisible. This is supposed to correspond to the intuitive "feel" of a mental state: highly discriminative and yet fundamentally integrated. Recent versions of the theory include a definition of qualia, which measures the geometric contribution of individual neural structures to the overall measure. In this paper, we examine these approaches from two philosophical perspectives, enactivism (externalism) and phenomenal states (internalism). We suggest that a promising enactivist response is to agree with Tononi that consciousness consists of integrated information, but to argue for a radical rethink about the nature of information itself. We argue that information is most naturally viewed as a three-place relation, involving a Bayesian-rational subject, the subject's evidence and the world (as brought under the subject's evolving understanding). To have (or gain) information is to behave in a Bayesian-rational way in response to evidence. Information only ever belongs to whole, rationally behaving agents; information is only "in the brain" from the point of view of a theorist seeking to explain behavior. Rational behavior (hence information) will depend on brain, body and world — embodiment matters. Then, from a phenomenal states perspective, we examine the way that internal states of a network can be not only unique and indivisible but also reflect this coherence as it might exist in an external world. Extending previously published material, we propose that two systems could both score well on traditional integration measures where one had meaningful world-representing states and the other did not. A model which involves iconic learning and depiction is discussed and tested in order to show how internal states can be about the world and how measures of integration influence this process. This retains some of the structure of Tononi's integration measurements but operates within sets of states of the world as filtered by receptors and repertoires of internal states achieved by depiction. This suggests a formalization of qualia which does not ignore world-reflecting content and relates to internal states that aid the conscious organism's ability to act appropriately in the world of which it is conscious. Thus, a common theme emerges: Tononi has good intuition about the necessary nature of consciousness, but his is not the only theory of experience able to do justice to these key intuitions. Tononi's theory has an apparent weakness, in that it treats conscious "information" as something intrinsically meaningless (i.e., without any necessary connection to the world), whereas both the approaches canvassed here naturally relate experienced information to the world.
[1]
J. Keynes.
A Treatise on Probability.
,
1923
.
[2]
C. E. SHANNON,et al.
A mathematical theory of communication
,
1948,
MOCO.
[3]
D. Dennett.
The Intentional Stance.
,
1987
.
[4]
C. Ray Smith,et al.
Maximum-entropy and Bayesian methods in science and engineering
,
1988
.
[5]
R. T. Cox.
Probability, frequency and reasonable expectation
,
1990
.
[6]
J. Shear,et al.
Pure consciousness: Scientific exploration of meditation techniques
,
1999
.
[7]
Olaf Sporns,et al.
Measuring information integration
,
2003,
BMC Neuroscience.
[8]
Randall D. Beer,et al.
The Dynamics of Active Categorical Perception in an Evolved Model Agent
,
2003,
Adapt. Behav..
[9]
T. Metzinger.
Being No One: The Self-Model Theory of Subjectivity
,
2004
.
[10]
E. Jaynes.
Probability theory : the logic of science
,
2003
.
[11]
R. Baierlein.
Probability Theory: The Logic of Science
,
2004
.
[12]
Eduardo Izquierdo-Torres,et al.
Is an Embodied System Ever Purely Reactive?
,
2005,
ECAL.
[13]
Andy Clark,et al.
Doing without representing?
,
1994,
Synthese.
[14]
R. Manzotti,et al.
Artificial Consciousness
,
2007
.
[15]
Igor Aleksander,et al.
Depictive architectures for synthetic phenomenology
,
2007
.
[16]
Giulio Tononi,et al.
Integrated Information in Discrete Dynamical Systems: Motivation and Theoretical Framework
,
2008,
PLoS Comput. Biol..
[17]
G. Tononi.
Consciousness as Integrated Information: a Provisional Manifesto
,
2008,
The Biological Bulletin.
[18]
Amos J. Storkey,et al.
A brief introduction to Weightless Neural Systems
,
2009,
ESANN.
[19]
M. James,et al.
An Analysis of Qualitative Feel as the Introspectible Subjective Aspect of a Space of Reasons
,
2009
.
[20]
Giulio Tononi,et al.
Qualia: The Geometry of Integrated Information
,
2009,
PLoS Comput. Biol..
[21]
Igor Aleksander,et al.
Iconic Training and Effective Information: Evaluating Meaning in Discrete Neural Networks
,
2009,
AAAI Fall Symposium: Biologically Inspired Cognitive Architectures.
[22]
Anil K. Seth,et al.
Explanatory Correlates of Consciousness: Theoretical and Computational Challenges
,
2009,
Cognitive Computation.
[23]
Anil K. Seth,et al.
Practical Measures of Integrated Information for Time-Series Data
,
2011,
PLoS Comput. Biol..