Month: May 2025

Adversarial testing of global neuronal workspace and integrated information theories of consciousness

Cogitate Consortium, Oscar Ferrante, Urszula Gorska-Klimowska, Simon Henin, Rony Hirschhorn, Aya Khalaf, Alex Lepauvre, Ling Liu, David Richter, Yamil Vidal, Niccolò Bonacchi, Tanya Brown, Praveen Sripad, Marcelo Armendariz, Katarina Bendtz, Tara Ghafari, Dorottya Hetenyi, Jay Jeschke, Csaba Kozma, David R. Mazumder, Stephanie Montenegro, Alia Seedat, Abdelrahman Sharafeldin, Shujun Yang, Sylvain Baillet, David J. Chalmers, Radoslaw M. Cichy, Francis Fallon, Theofanis I. Panagiotaropoulos, Hal Blumenfeld, Floris P. de Lange, Sasha Devore, Ole Jensen, Gabriel Kreiman, Huan Luo, Melanie Boly, Stanislas Dehaene, Christof Koch, Giulio Tononi, Michael Pitts, Liad Mudrik & Lucia Melloni

Nature (2025)

Different theories explain how subjective experience arises from brain activity1,2. These theories have independently accrued evidence, but have not been directly compared3. Here we present an open science adversarial collaboration directly juxtaposing integrated information theory (IIT)4,5 and global neuronal workspace theory (GNWT)6,7,8,9,10 via a theory-neutral consortium11,12,13. The theory proponents and the consortium developed and preregistered the experimental design, divergent predictions, expected outcomes and interpretation thereof12. Human participants (n = 256) viewed suprathreshold stimuli for variable durations while neural activity was measured with functional magnetic resonance imaging, magnetoencephalography and intracranial electroencephalography. We found information about conscious content in visual, ventrotemporal and inferior frontal cortex, with sustained responses in occipital and lateral temporal cortex reflecting stimulus duration, and content-specific synchronization between frontal and early visual areas. These results align with some predictions of IIT and GNWT, while substantially challenging key tenets of both theories. For IIT, a lack of sustained synchronization within the posterior cortex contradicts the claim that network connectivity specifies consciousness. GNWT is challenged by the general lack of ignition at stimulus offset and limited representation of certain conscious dimensions in the prefrontal cortex. These challenges extend to other theories of consciousness that share some of the predictions tested here14,15,16,17. Beyond challenging the theories, we present an alternative approach to advance cognitive neuroscience through principled, theory-driven, collaborative research and highlight the need for a quantitative framework for systematic theory testing and building.

Read the full article at: www.nature.com

DOMAINS OF LAWS YET DOMAINS OF NO LAW: Energy and Work, Responsible Free Will Choice and Doing

Sudip Patra and Stuart Kauffman

We explore here the fundamental and striking paradigmatic shifts between ‘Domain of Laws’ and ‘Domain of No Laws’, where the former is an apt encapsulation of our remarkably successful but orthodox science world view (including classical physics and quantum mechanics) with well- defined and stable configuration spaces having deterministic or stochastic evolution, and the latter is a radically new Domain of No Law with evolving configuration spaces, non-deducible information creation, genuine novelties and an un-prestatable Adjacent Possible. We explore the features of these two distinct domains asking what can be defined with respect to work, energy, entropy, and agency. We offer a reconstruction of quantum mechanics to reframe traditional assumptions and address lingering questions concerning the nature of living, complex adaptive systems. We propose that a genuine responsible free will and a central role of agency are essential features of an evolving Biosphere. Here we extend this theme to call for a radically new and comprehensive view of science itself.

Read the full article at: osf.io

Partisan disparities in the use of science in policy

ALEXANDER C. FURNAS, TIMOTHY M. LAPIRA, AND DASHUN WANG
SCIENCE 24 Apr 2025 Vol 388, Issue 6745 pp. 362-367 DOI: 10.1126/science.adt9895

Science has long been regarded as essential to policy-making, serving as one of the primary sources of evidence that informs decisions (1, 2) with its particular epistemic authority (3). Its role has become especially vital, as many pressing societal challenges today—from climate change to public health crises to technological advancement—are intricately linked with scientific progress. However, amid rising political polarization (4), a fundamental question remains open: Is science used differently by policy-makers in different parties? Here we combine two large-scale databases capturing policy, science, and their interactions to examine the partisan differences in citing science in policy-making in the United States. Overall, we observe systematic differences in the amount, content, and character of science cited in policy by partisan factions in the United States. These differences are strikingly persistent across fields of research, policy issues, time, and institutional contexts.

Read the full article at: www.science.org

Mathematical and Computational Methods for Complex Social Systems

Heather Z. Brooks, Michelle Feng, Mason A. Porter, and Alexandria Volkening

The spread of memes and misinformation on social media, political redistricting, gentrification in urban communities, pedestrian movement in crowds, and the dynamics of voters are among the many social phenomena that researchers investigate in the field of complex systems. In the study of complex social systems, there is often also societal relevance to improving our understanding of how individuals interact with each other and their environment, giving rise to collective group dynamics.

The mathematical and computational study of complex social systems relies on and motivates the development of methods in many topics, including mathematical modeling, data analysis, network science, and topology and geometry. This volume is a collection of diverse articles about complex social systems. This collection includes both (1) survey and tutorial articles that introduce complex social systems and methods to study them and (2) manuscripts with original research that highlight a variety of mathematical areas and applications.

This book introduces the study of complex social systems to a broad mathematical audience. It will particularly appeal to people who are interested in applied mathematics.

Read the full article at: www.ams.org

Structural Cellular Hash Chemistry

Hiroki Sayama

2025 IEEE Symposium on Computational Intelligence in Artificial Life and Cooperative Intelligent Systems (ALIFE-CIS)

Hash Chemistry, a minimalistic artificial chemistry model of open-ended evolution, has recently been extended to non-spatial and cellular versions. The non-spatial version successfully demonstrated continuous adaptation and unbounded growth of complexity (size) of self-replicating entities, but it did not simulate multiscale ecological interactions among the entities. On the contrary, the cellular version explicitly represented multiscale spatial ecological interactions among evolving patterns, yet it failed to show meaningful adaptive evolution or complexity growth. It remains an open question whether it is possible to create a similar minimalistic evolutionary system that can exhibit all of those desired properties at once, within a computationally efficient framework. Here we propose an improved version of Cellular Hash Chemistry, called “Structural Cellular Hash Chemistry” (SCHC). In SCHC, individual identities of evolving patterns are explicitly represented and processed as the connected components of the nearest neighbor graph of active (non-empty) cells. The neighborhood connections are established by connecting active cells with other active cells in their Moore neighborhoods in a 2D cellular grid. Evolutionary dynamics in SCHC are simulated via pairwise competitions of two randomly selected patterns, following the approach used in the non-spatial Hash Chemistry. SCHC’s computational cost was significantly less than the original and non-spatial versions. Numerical simulations showed that these model modifications achieved spontaneous movement, self-replication and unbounded growth of complexity (size) of spatial evolving patterns, which were clearly visible in space in a highly intuitive manner. Detailed analysis of simulation results showed that there were spatial ecological interactions among self-replicating patterns and their diversity was also substantially promoted in SCHC, neither of which was present in the non-spatial version.

Read the full article at: ieeexplore.ieee.org