PLoS ONE
May 13, 2015
Melanie Boly, Shuntaro Sasai, Olivia Gosseries et al.
69 citations
A meaningful sequence of stimuli, like movie frames, triggers varied experiences, while meaningless stimuli, like TV noise, produce a uniform experience despite physical differences. The differentiation of cortical responses, measured by Lempel-Ziv complexity of functional MRI images, reflects the overall meaningfulness of a stimulus set rather than differences among stimuli. Brain activity patterns showed highest differentiation during a movie, intermediate for a temporally scrambled movie, and minimal for spatially scrambled TV noise, even though overall cortical activation was strong and widespread in all conditions. Meaningfulness also correlated with higher information integration among cortical regions. This approach can assess stimulus meaningfulness without identifying relevant features or neural locations.
Entropy
February 11, 2023
William Marshall, Matteo Grasso, William G. P. Mayner et al.
19 citations
Integrated information theory (IIT) proposes that consciousness is identical to the cause-effect structure generated by a maximally irreducible substrate (a Φ-structure). This work introduces a definition for system-integrated information (φs) grounded in IIT's postulates of existence, intrinsicality, information, and integration. It examines how determinism, degeneracy, and connectivity fault lines affect system-integrated information. The proposed measure identifies complexes as systems whose φs exceeds that of any overlapping candidate systems.
Frontiers in computational neuroscience
January 1, 2024
Rousslan Fernand Julien Dossa, Kai Arulkumaran, Arthur Juliani et al.
An embodied agent with a structure based on global workspace theory, trained on realistic audiovisual inputs to navigate 3D environments, performs better and more robustly at smaller working memory sizes compared to a standard recurrent architecture. Task complexity and regularization are essential for feature learning and the development of meaningful attentional patterns within the workspace.
arXiv Preprint Archive
March 24, 2022
Arthur Juliani, Kai Arulkumaran, Shuntaro Sasai et al.
The authors examine three contemporary theories of conscious function—Global Workspace Theory, Information Generation Theory, and Attention Schema Theory—and find that each relates conscious function to some aspect of domain-general intelligence in humans. They then observe that state-of-the-art deep learning methods have begun incorporating key aspects of these theories, though they remain far from demonstrating general intelligence. Using mental time travel in humans as a motivating example, the authors propose combining insights from all three theories into a single unified model. Such artificial agents would possess greater general intelligence and align more closely with current understanding of consciousness's functional role, making this a promising near-term AI research goal.