Is Consciousness Computable? Quantifying Integrated Information Using Algorithmic Information Theory

In this article we review Tononi's (2008) theory of consciousness as integrated information. We argue that previous formalizations of integrated information (e.g. Griffith, 2014) depend on information loss. Since lossy integration would necessitate continuous damage to existing memories, we propose it is more natural to frame consciousness as a lossless integrative process and provide a formalization of this idea using algorithmic information theory. We prove that complete lossless integration requires noncomputable functions. This result implies that if unitary consciousness exists, it cannot be modelled computationally.Comment: Maguire, P., Moser, P., Maguire, R. & Griffith, V. (2014). Is consciousness computable? Quantifying integrated information using algorithmic information theory. In P. Bello, M. Guarini, M. McShane, & B. Scassellati (Eds.), Proceedings of the 36th Annual Conference of the Cognitive Science Society. Austin, TX: Cognitive Science Societ

Consciousness and information integration

Integration information theories posit that the integration of information is necessary and/or sufficient for consciousness. In this paper, we focus on three of the most prominent information integration theories: Information Integration Theory, Global Workspace Theory, and Attended Intermediate-Level Theory. We begin by explicating each theory and key concepts they utilize. We then argue that the current evidence indicates that the integration of information is neither necessary nor sufficient for consciousness. Unlike GWT and AIR, IIT maintains that conscious experience is both necessary and sufficient for consciousness. We present empirical evidence indicating that simple features are experienced in the absence of feature integration and argue that it challenges IIT’s necessity claim. In addition, we challenge IIT’s sufficiency claim by presenting evidence from hemineglect cases and amodal completion indicating that contents may be integrated and yet fail to give rise to subjective experience. Moreover, we present empirical evidence from subjects with frontal lesions who are unable to carry out simple instructions and argue that they are irreconcilable with GWT. Lastly, we argue that empirical evidence indicating that patients with visual agnosia fail to identify objects they report being conscious of present a challenge to AIR’s necessity claim

Propofol Induction Reduces the Capacity for Neural Information Integration: Implications for the Mechanism of Consciousness and General Anesthesia

The cognitive unbinding paradigm suggests that the synthesis of cognitive information is attenuated by general anesthesia. Here, we investigated the functional organization of brain activities in the conscious and anesthetized states, based on characteristic functional segregation and integration of electroencephalography (EEG). EEG recordings were obtained from 14 subjects undergoing induction of general anesthesia with propofol. We quantified changes in mean information integration capacity in each band of the EEG. After induction with propofol, mean information integration capacity was reduced most prominently in the gamma band of the EEG (p=0.0001). Furthermore, we demonstrate that loss of consciousness is reflected by the breakdown of the spatiotemporal organization of gamma waves. Induction of general anesthesia with propofol reduces the capacity for information integration in the brain. These data directly support the information integration theory of consciousness and the cognitive unbinding paradigm of general anesthesia

The informational mind and the information integration theory of consciousness

According to Aleksander and Morton’s informational mind hypothesis, conscious minds are state structures that are created through iconic learning. Distributed representations of colors, edges, objects, etc. are linked with proprioceptive and motor information to generate the awareness of an out-there world. The uniqueness and indivisibility of these iconically learnt states reflect the uniqueness and indivisibility of the world. This article summarizes the key claims of the informational mind hypothesis and considers them in relation to Tononi’s information integration theory of consciousness. Some suggestions are made about how the informational mind hypothesis could be experimentally tested, and its significance for work on machine consciousness is considered

Measuring integrated information from the decoding perspective

Accumulating evidence indicates that the capacity to integrate information in the brain is a prerequisite for consciousness. Integrated Information Theory (IIT) of consciousness provides a mathematical approach to quantifying the information integrated in a system, called integrated information, $\Phi$. Integrated information is defined theoretically as the amount of information a system generates as a whole, above and beyond the sum of the amount of information its parts independently generate. IIT predicts that the amount of integrated information in the brain should reflect levels of consciousness. Empirical evaluation of this theory requires computing integrated information from neural data acquired from experiments, although difficulties with using the original measure $\Phi$ precludes such computations. Although some practical measures have been previously proposed, we found that these measures fail to satisfy the theoretical requirements as a measure of integrated information. Measures of integrated information should satisfy the lower and upper bounds as follows: The lower bound of integrated information should be 0 when the system does not generate information (no information) or when the system comprises independent parts (no integration). The upper bound of integrated information is the amount of information generated by the whole system and is realized when the amount of information generated independently by its parts equals to 0. Here we derive the novel practical measure $\Phi^*$ by introducing a concept of mismatched decoding developed from information theory. We show that $\Phi^*$ is properly bounded from below and above, as required, as a measure of integrated information. We derive the analytical expression $\Phi^*$ under the Gaussian assumption, which makes it readily applicable to experimental data

Efficient Algorithms for Searching the Minimum Information Partition in Integrated Information Theory

The ability to integrate information in the brain is considered to be an essential property for cognition and consciousness. Integrated Information Theory (IIT) hypothesizes that the amount of integrated information ($\Phi$) in the brain is related to the level of consciousness. IIT proposes that to quantify information integration in a system as a whole, integrated information should be measured across the partition of the system at which information loss caused by partitioning is minimized, called the Minimum Information Partition (MIP). The computational cost for exhaustively searching for the MIP grows exponentially with system size, making it difficult to apply IIT to real neural data. It has been previously shown that if a measure of $\Phi$ satisfies a mathematical property, submodularity, the MIP can be found in a polynomial order by an optimization algorithm. However, although the first version of $\Phi$ is submodular, the later versions are not. In this study, we empirically explore to what extent the algorithm can be applied to the non-submodular measures of $\Phi$ by evaluating the accuracy of the algorithm in simulated data and real neural data. We find that the algorithm identifies the MIP in a nearly perfect manner even for the non-submodular measures. Our results show that the algorithm allows us to measure $\Phi$ in large systems within a practical amount of time

Human Conscious Experience is Four-Dimensional and has a Neural Correlate Modeled by Einstein's Special Theory of Relativity

In humans, knowing the world occurs through spatial-temporal experiences and interpretations. Conscious experience is the direct observation of conscious events. It makes up the content of consciousness. Conscious experience is organized in four dimensions. It is an orientation in space and time, an understanding of the position of the observer in space and time. A neural correlate for four-dimensional conscious experience has been found in the human brain which is modeled by Einstein’s Special Theory of Relativity. Spacetime intervals are fundamentally involved in the organization of coherent conscious experiences. They account for why conscious experience appears to us the way it does. They also account for assessment of causality and past-future relationships, the integration of higher cognitive functions, and the implementation of goal-directed behaviors. Spacetime intervals in effect compose and direct our conscious life. The relativistic concept closes the explanatory gap and solves the hard problem of consciousness (how something subjective like conscious experience can arise in something physical like the brain). There is a place in physics for consciousness. We describe all physical phenomena through conscious experience, whether they be described at the quantum level or classical level. Since spacetime intervals direct the formation of all conscious experiences and all physical phenomena are described through conscious experience, the equation formulating spacetime intervals contains the information from which all observable phenomena may be deduced. It might therefore be considered expression of a theory of everything

The informational mind and the information integration theory of consciousness

According to Aleksander and Morton’s informational mind hypothesis, conscious minds are state structures that are created through iconic learning. Distributed representations of colors, edges, objects, etc. are linked with proprioceptive and motor information to generate the awareness of an out-there world. The uniqueness and indivisibility of these iconically learnt states reflect the uniqueness and indivisibility of the world. This article summarizes the key claims of the informational mind hypothesis and considers them in relation to Tononi’s information integration theory of consciousness. Some suggestions are made about how the informational mind hypothesis could be experimentally tested, and its significance for work on machine consciousness is considered