| Frontiers in Psychology | |
| Integrated Information and State Differentiation | |
| William Marshall1  | |
| 关键词: integrated information theory; state differentiation; cause-effect power; animats; consciousness; | |
| DOI : 10.3389/fpsyg.2016.00926 | |
| 学科分类:心理学(综合) | |
| 来源: Frontiers | |
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【 摘 要 】
Integrated information (Φ) is a measure of the cause-effect power of a physical system. This paper investigates the relationship between Φ as defined in Integrated Information Theory and state differentiation (D), the number of, and difference between potential system states. Here we provide theoretical justification of the relationship between Φ and D, then validate the results using a simulation study. First, we show that a physical system in a state with high Φ necessarily has many elements and specifies many causal relationships. Furthermore, if the average value of integrated information across all states is high, the system must also have high differentiation. Next, we explore the use of D as a proxy for Φ using artificial networks, evolved to have integrated structures. The results show a positive linear relationship between Φ and D for multiple network sizes and connectivity patterns. Finally we investigate the differentiation evoked by sensory inputs and show that, under certain conditions, it is possible to estimate integrated information without a direct perturbation of its internal elements. In concluding, we discuss the need for further validation on larger networks and explore the potential applications of this work to the empirical study of consciousness, especially concerning the practical estimation of Φ from neuroimaging data.
【 授权许可】
CC BY
【 预 览 】
| Files | Size | Format | View |
|---|---|---|---|
| RO201904023587785ZK.pdf | 1968KB |
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