Mechanism Integrated Information

Barbosa, Leonardo S.; Marshall, William; Albantakis, Larissa; Tononi, Giulio

doi:10.3390/e23030362

Cited by 37 publications

(110 citation statements)

References 25 publications

(48 reference statements)

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“… 5 For the mathematical details of computing causal distinctions, see Barbosa et al (2021) ; for causal relations, see Haun and Tononi (2019) . The cause-effect structures of the two systems are unfolded using PyPhi ( Mayner et al 2018 ).…”

Section: Footnotesmentioning

confidence: 99%

Of maps and grids

Grasso

Haun

Tononi

2021

Neuroscience of Consciousness

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Neuroscience has made remarkable advances in accounting for how the brain performs its various functions. Consciousness, too, is usually approached in functional terms: the goal is to understand how the brain represents information, accesses that information, and acts on it. While useful for prediction, this functional, information-processing approach leaves out the subjective structure of experience: it does not account for how experience feels. Here, we consider a simple model of how a “grid-like” network meant to resemble posterior cortical areas can represent spatial information and act on it to perform a simple “fixation” function. Using standard neuroscience tools, we show how the model represents topographically the retinal position of a stimulus and triggers eye muscles to fixate or follow it. Encoding, decoding, and tuning functions of model units illustrate the working of the model in a way that fully explains what the model does. However, these functional properties have nothing to say about the fact that a human fixating a stimulus would also “see” it—experience it at a location in space. Using the tools of Integrated Information Theory, we then show how the subjective properties of experienced space—its extendedness—can be accounted for in objective, neuroscientific terms by the “cause-effect structure” specified by the grid-like cortical area. By contrast, a “map-like” network without lateral connections, meant to resemble a pretectal circuit, is functionally equivalent to the grid-like system with respect to representation, action, and fixation but cannot account for the phenomenal properties of space.

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Section: Footnotesmentioning

confidence: 99%

Of maps and grids

Grasso

Haun

Tononi

2021

Neuroscience of Consciousness

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“…Many of these measures have been conceived as precursory or empirical versions of quantities proposed within the integrated information theory (IIT) of consciousness [45][46][47][48]. Theory-based measures of integrated information (ϕ and Φ) are, however, intended to be causal, rather than informational measures, meaning they rely on perturbational rather than observed data [46,47,49] and will thus be discussed in the next section.…”

Section: Information Theoretical Measuresmentioning

confidence: 99%

Quantifying the Autonomy of Structurally Diverse Automata: A Comparison of Candidate Measures

Albantakis

2021

Entropy

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Should the internal structure of a system matter when it comes to autonomy? While there is still no consensus on a rigorous, quantifiable definition of autonomy, multiple candidate measures and related quantities have been proposed across various disciplines, including graph-theory, information-theory, and complex system science. Here, I review and compare a range of measures related to autonomy and intelligent behavior. To that end, I analyzed the structural, information-theoretical, causal, and dynamical properties of simple artificial agents evolved to solve a spatial navigation task, with or without a need for associative memory. By contrast to standard artificial neural networks with fixed architectures and node functions, here, independent evolution simulations produced successful agents with diverse neural architectures and functions. This makes it possible to distinguish quantities that characterize task demands and input-output behavior, from those that capture intrinsic differences between substrates, which may help to determine more stringent requisites for autonomous behavior and the means to measure it.

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“…That is not to say such information is not relevant at some stage of explanation but merely that it is not one of the essential features to explain when considering how a system is conscious from the intrinsic perspective. More recently, Barbosa et al [ 27 ] and Barbosa et al [ 28 ] have developed a unique distance measure for intrinsic information, derived from the postulates of Integrated Information Theory (IIT) of consciousness (a short introduction to IIT will be given in Section 5 ). The basic idea is to capture not just the amount/value of information in the system, but the quality of that information in spite of a sender/receiver, i.e., what information is held intrinsically for the system.…”

Section: From Syntax To Semantics Towards Intrinsic Informationmentioning

confidence: 99%

“…That being said, I do want to touch on two important aspects of IIT as it relates to the present topic, that is (1) the cause–effect structure (CES) posited by IIT (quantified by Φ max≥ ) and (2) the process and purpose of identifying mechanisms (quantified as φ Max ) and their relations (to what extent the mechanisms cause–effect repertoires overlap with one another) within the IIT framework. This will be something of an incomplete explanation of IIT for the sake of brevity and focus; if one wants a thorough and exhaustive overview of the contents of IIT, I would recommend reading the papers that most accurately reflect the substantive changes that amount to IIT 4.0 [ 11 , 14 , 27 , 28 , 45 , 46 ], which present developments and refinements since IIT 3.0 [ 10 ]. Despite this, I will endeavor to give all the necessary details as it relates to the overall aim of this essay.…”

Section: Iit Intrinsic Structure and Dynamics And Approaching The Hard Problemmentioning

confidence: 99%

“…IIT looks to find those causal/informational relationships that form irreducible sets, that is elements that form an integrated whole, where the loss of some element affects the amount of information the group of elements taken together express (integrated information). The most recent formal expression of this value can be found in Barbosa et al [ 27 ] and Barbosa et al [ 28 ] the unique distance measure developed therein will be the formalism used for the updated IIT 4.0 version of the theory currently in development. The idea being, that finding such irreducible sets reveals how the current state of the system shows you what states they were in in the past and how they constrain future states of the system, this is given by the transition probability matrix (TPM) of all the units in the candidate system at a time.…”

Section: Iit Intrinsic Structure and Dynamics And Approaching The Hard Problemmentioning

confidence: 99%

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Not All Structure and Dynamics Are Equal

Mindt

2021

Entropy

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The hard problem of consciousness has been a perennially vexing issue for the study of consciousness, particularly in giving a scientific and naturalized account of phenomenal experience. At the heart of the hard problem is an often-overlooked argument, which is at the core of the hard problem, and that is the structure and dynamics (S&D) argument. In this essay, I will argue that we have good reason to suspect that the S&D argument given by David Chalmers rests on a limited conception of S&D properties, what in this essay I’m calling extrinsic structure and dynamics. I argue that if we take recent insights from the complexity sciences and from recent developments in Integrated Information Theory (IIT) of Consciousness, that we get a more nuanced picture of S&D, specifically, a class of properties I’m calling intrinsic structure and dynamics. This I think opens the door to a broader class of properties with which we might naturally and scientifically explain phenomenal experience, as well as the relationship between syntactic, semantic, and intrinsic notions of information. I argue that Chalmers’ characterization of structure and dynamics in his S&D argument paints them with too broad a brush and fails to account for important nuances, especially when considering accounting for a system’s intrinsic properties. Ultimately, my hope is to vindicate a certain species of explanation from the S&D argument, and by extension dissolve the hard problem of consciousness at its core, by showing that not all structure and dynamics are equal.

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Mechanism Integrated Information

Cited by 37 publications

References 25 publications

Of maps and grids

Of maps and grids

Quantifying the Autonomy of Structurally Diverse Automata: A Comparison of Candidate Measures

Not All Structure and Dynamics Are Equal

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