Léo PioLopez

Complex systems, embodied cognition, AI, networks

[Michael Levin @drmichaellevin]

@bryan_johnson 🙏 It absolutely has implications for longevity, not only for individuals (https://t.co/Jn1QCeRR1A) but for species-level "don't die" (https://t.co/HEs4mFH4is), and the paradox of change.

[Michael Levin @drmichaellevin]

New #preprint reviewing and conceptually mapping the major theories in the field of aging (@LPiolopez, Navneet Jawanda)

"Theories of Aging: From Damage and Programmed Theories to Goal-Directedness"

https://t.co/q7phOY4YOL

"Aging is an extensive biological process characterized by morphological and functional alterations at different biological scales, resulting in a systematic decline in biological functions ultimately leading to death. Overall, two main types of theories have been proposed: damage-based theories and programmatic theories. We propose a third option, framed in the cognitive perspective on multiscale biological systems. Here, we review the different theories of aging, organize them in a conceptual hierarchy, and integrate our new model within the existing frameworks: aging as a consequence of loss of goal-directedness (in anatomical space). In this model, aging is driven by a dynamical systems-level disruption of homeostatic alignment within cellular collectives that build and repair a healthy body during development and maturation. In this model, morphogenesis is a homeostatic (goal-seeking) process; left with no goals after the developmental phase has been completed, aging can occur in the absence of damage via the functional disbanding of body components from their original aligned goal state. We suggest a roadmap with important implications for regenerative medicine and aging."

[hartl.bene @BeneHartl]

Our work on

Symbiogenesis: from Barricelli's Legacy to Collective Intelligence

is out in its final form: https://t.co/C2wgxjxexK

from ALICE to GECCO 26, together with J. Ashford, B. Sakallioglu, M Tataryn, A. Valerio, @LPiolopez, @marko_cvjetko, R. Löffler, and @stenichele

[Michael Levin @drmichaellevin]

New #preprint @LPiolopez @BenjaminLy61243

https://t.co/yDzBbbQI6Q

"Alignment Is to a Virtual Governor: A Theory of Coordination in Diverse Intelligence"

Abstract: Alignment is a central problem in systems composed of diverse, interacting components, from biological development to social and engineered systems. One crucial aspect of this problem is determining an answer to the question of to whom or to what the alignment should be. We argue that in decentralized systems, alignment is necessarily to a virtual governor, an abstract governing entity embodied in the coordinating relationships among agents, such as bioelectric networks or the price system. Crucially, despite not being a physical object, virtual governors are causally instructive, controlling the behavior of a system by aligning its parts toward higher-level goals. As a result, agents, from cells to humans and all manner of diverse intelligences, behave as if pursuing the objectives of the virtual governor. We argue that alignment is necessarily to a virtual governor in decentralized, coordinated systems, discuss examples of virtual governors, and describe how virtual governors are constructed by the very components they align.

[Foresight Institute @foresightinst]

Meet Léo Pio-Lopez: computational biologist, Affiliate SeniorScientist at the Allen Discovery Center at @TuftsUniversity, and Foresight Fellow 2026.

Léo’s research spans three closely related areas: the cognition of morphogenetic systems, the bioinformatics of xenobots, regeneration, cancer, and aging, and the design of new AI architectures inspired by biological principles.

He explores the question of what life is actually computing, and seeks to use the answer to expand the frontiers of regenerative medicine and AI with applications in aging and AI alignment.

[Michael Levin @drmichaellevin]

New #preprint: @BeneHartl @LPiolopez

https://t.co/3yrxPGIKAw

"BraiNCA: brain-inspired neural cellular automata and applications to morphogenesis and motor control"

Abstract:

Most of the Neural Cellular Automata (NCAs) defined in the literature have a common theme: they are based on regular grids with a Moore neighborhood (one-hop neighbour). They do not take into account long-range connections and more complex topologies as we can find in the brain. In this paper, we introduce BraiNCA, a brain-inspired NCA with an attention layer, long-range connections and complex topology. BraiNCAs shows better results in terms of robustness and speed of learning on the two tasks compared to Vanilla NCAs establishing that incorporating attention-based message selection together with explicit long-range edges can yield more sample-efficient and damage-tolerant self-organization than purely local, grid-based update rules. These results support the hypothesis that, for tasks requiring distributed coordination over extended spatial and temporal scales, the choice of interaction topology and the ability to dynamically route information will impact the robustness and speed of learning of an NCA. More broadly, BraiNCA provides brain-inspired NCA formulation that preserves the decentralized local update principle while better reflecting non-local connectivity patterns, making it a promising substrate for studying collective computation under biologically-realistic network structure and evolving cognitive substrates.

[Stefano Nichele @stenichele]

What can a 70-year-old idea about digital organisms teach us about the future of AI and artificial life? 🧬💡

📄 Read our report: https://t.co/pIJjL1WaWT

#ArtificialLife #ComplexSystems #OpenEndedEvolution #ArtificialIntelligence #ALife

[Michael Levin @drmichaellevin]

New preprint with @LPiolopez :

https://t.co/g71arOsLlc

"Multi-Scale Longevity: Defeating Aging from Cells to Embodied Human Minds, and the Future of the Species"

a broader view of longevity research, an invited chapter for an upcoming volume titled "Frontiers of Longevity Science" published by Springer Nature.

Abstract: "Aging is a fundamental biological process characterized by morphological and functional decline ultimately leading to death. Current research in aging is directed toward extending both healthspan and lifespan by elucidating the molecular and cellular mechanisms that drive aging and by developing interventions capable of delaying, preventing, or reversing age-associated physiological decline and multimorbidity. In this chapter, we take a broader view beyond the healthspan and lifespan of individuals, to consider deep issues impacting the duration and nature of our embodiment, including the nature of change, the meaning of personal persistence, and the future of humanity at multiple scales. If you don’t change, you die out (or become irrelevant); but if you change, are you still present? We argue that aging, like traumatic injury and cancer, is a fundamental challenge to an embodied mind seeking to maintain its distinct nature, differentiated from the environment. Understanding aging thus must take place within the context of a broader story of how biological individuals come to exist, how they continue to exist despite continual challenge, and how their plasticity can be leveraged for transformative change beyond mere persistence. Here, we will present our aging framework grounded in the collective intelligence of cells, then we will discuss the implication for the human- and the species-level aspects of artificial chimerism and its corollary - multiscale (non-Darwinian) evolution. We conclude with some important open questions for humanity with respect to the implications of rejuvenation and longevity technologies."

[Michael Levin @drmichaellevin]

New preprint: https://t.co/8tCMPK7AlH
Chris Fields, @BeneHartl, @LPiolopez
"Remapping and navigation of an embedding space via error minimization: a fundamental organizational principle of cognition in natural and artificial systems"

Abstract:

The emerging field of diverse intelligence seeks an integrated view of problem-solving in agents of very different provenance, composition, and substrates. From subcellular chemical networks to swarms of organisms, and across evolved, engineered, and chimeric systems, it is hypothesized that scale-invariant principles of decision-making can be discovered. We propose that cognition in both natural and synthetic systems can be characterized and understood by the interplay between two equally important invariants: (1) the remapping of embedding spaces, and (2) the navigation within these spaces. Biological collectives, from single cells to entire organisms (and beyond), remap transcriptional, morphological, physiological, or 3D spaces to maintain homeostasis and regenerate structure, while navigating these spaces through distributed error correction. Modern Artificial Intelligence (AI) systems, including transformers, diffusion models, and neural cellular automata enact analogous processes by remapping data into latent embeddings and refining them iteratively through contextualization. We argue that this dual principle - remapping and navigation of embedding spaces via iterative error minimization - constitutes a substrate-independent invariant of cognition. Recognizing this shared mechanism not only illuminates deep parallels between living systems and artificial models, but also provides a unifying framework for engineering adaptive intelligence across scales.

[hartl.bene @BeneHartl]

Extremely humbled that our recent review on "Neural Cellular Automata: Applications in Biology and Beyond Classical AI" is trending #1 in #Biophysics!!

Check out the paper (with @LPiolopez and @drmichaellevin) here:
https://t.co/1D0eq6v34P

[Michael Levin @drmichaellevin]

Final version is out: @LPiolopez
https://t.co/oXXnl1lPO8

"Atavistic Genetic Expression Dissociation (AGED) DuringAging: Meta-Phylostratigraphic Evidence of Cellular andTissue-Level Phylogenetic Dissociation"

Abstract: "... We propose an atavistic dysregulation of gene expression at cellular and tissue levels during aging, framing aging as a gradual regression toward ancestral cellular states. Similarly to the atavistic model of cancer, in which cells revert to unicellular-like behavior, aging may result from the breakdown of coordinated morphogenetic control, leading organs and tissues toward less integrated, ancient unicellular states. We suggest that aging may involve a progressive reversal of the well-known ontogenetic tracing of prior phylogenetic embryonic characteristics. Moreover, aging could involve a loss of large-scale coordination, with tissues reverting to ancient gene expression to different degrees. We tested this hypothesis using a meta-phylostratigraphic analysis, finding: (1) An atavistic over-representation of differential expression in the most ancient genes and under-representation in the evolutionary youngest genes for two multi-tissue aging databases, and tissues covering skin, ovarian, immune, senescent and mesenchymal-senescent cells; (2) No significant atavistic over-representation of the differential gene expression during aging of brain cells and mesenchymal stem cells; (3) overall age-dependent increase of heterogeneity in the direction of the phylogenetic position of tissues' transcriptional profiles; (4) and an overall negative evolutionary age mean shift toward the most ancient genes. Our analyses suggest that aging involves uncoordinated and tissue-specific phylogenetic changes in gene expression. Understanding aging as a structured, heterogeneous atavistic process opens new avenues for rejuvenation, focusing on restoring multicellular coherence in evolutionarily youthful gene expression."

[hartl.bene @BeneHartl]

Thrilled to announce that our new paper on

"Neural cellular automata: Applications to biology and beyond classical AI"

is out in Physics of Life Reviews.

... work with @drmichaellevin and @LPiolopez

[Michael Levin @drmichaellevin]

Final version is out:

https://t.co/UKhwBNpb1W

"Neural cellular automata: Applications to biology and beyond classical AI"

@LPiolopez
Benedikt Hartl

"Neural Cellular Automata (NCA) represent a powerful framework for modeling biological self-organization, extending classical rule-based systems with trainable, differentiable (or evolvable) update rules that capture the adaptive self-regulatory dynamics of living matter. By embedding Artificial Neural Networks (ANNs) as local decision-making centers and interaction rules between localized agents, NCA can simulate processes across molecular, cellular, tissue, and system-level scales, offering a multiscale competency architecture perspective on evolution, development, regeneration, aging, morphogenesis, and robotic control. These models not only reproduce canonical, biologically inspired target patterns but also generalize to novel conditions, demonstrating robustness to perturbations and the capacity for open-ended adaptation and reasoning through embodiment. Given their immense success in recent developments, we here review current literature of NCAs that are relevant primarily for biological or bioengineering applications. Moreover, we emphasize that beyond biology, NCAs display robust and generalizing goal-directed dynamics without centralized control, e.g., in controlling or regenerating composite robotic morphologies or even on cutting-edge reasoning tasks such as ARC-AGI-1. In addition, the same principles of iterative state-refinement is reminiscent to modern generative Artificial Intelligence (AI), such as probabilistic diffusion models. Their governing self-regulatory behavior is constraint to fully localized interactions, yet their collective behavior scales into coordinated system-level outcomes. We thus argue that NCAs constitute a unifying computationally lean paradigm that not only bridges fundamental insights from multiscale biology with modern generative AI, but have the potential to design truly bio-inspired collective intelligence capable of hierarchical reasoning and control."

[Michael Levin @drmichaellevin]

Given the recent discussion about aging (and our approach to it) in https://t.co/sL9cRfXXEH, it might be worthwhile to mention that my perspective is:

birth defects, failure to regenerate complex organs after damage, cancer, degenerative disease, and aging are all *the same problem* at root. It is all about how living matter implements a collective intelligence to maintain a specific anatomy over time (whether regenerating from: 1 egg cell, a.k.a. embryogenesis, from a damaged tissue, or from the small-scale wear and tear of adult life), and how we can facilitate that process of renewal. Regeneration, in the broadest sense, is the answer to all of these problems. It is not going to be possible to accelerate (or prevent, for those who want to) anti-aging research without feeding (or squelching) these other aspects of medicine and basic science.

If you're truly arguing against longevity research, it's not just the elderly billionaires that you're targeting, it's also the kids with cancer, the people born with damaged organs, victims of injury, those damaged by pathogens, etc. etc. It's all the same pool of suffering, with the same root cause.

https://t.co/DdEhwS2yuO

[Michael Levin @drmichaellevin]

Final version is out: aging as the result of loss of goal-directedness

https://t.co/Vmm2zFQHzu

@BeneHartl @LPiolopez

"Although substantial advancements are made in manipulating lifespan in model organisms, the fundamental mechanisms driving aging remain elusive. No comprehensive computational platform is capable of making predictions on aging in multicellular systems. Focus is placed on the processes that build and maintain complex target morphologies, and develop an insilico model of multiscale homeostatic morphogenesis using Neural Cellular Automata (NCAs) trained by neuroevolution. In the context of this model: 1) Aging emerges after developmental goals are completed, even without noise or programmed degeneration; 2) Cellular misdifferentiation, reduced competency, communication failures, and genetic damage all accelerate aging but are not its primary cause; 3) Aging correlates with increased active information storage and transfer entropy, while spatial entropy distinguishes two dynamics, structural loss and morphological noise accumulation; 4) Despite organ loss, spatial information persists in tissue, implementing a memory of lost structures, which can be reactivated for organ restoration through targeted regenerative information; and 5) rejuvenation is found to be most efficient when regenerative information includes differential patterns of affected cells and their neighboring tissue, highlighting strategies for rejuvenation. This model suggests a novel perspective on aging caused by loss of goal-directedness, with potentially significant implications for longevity research and regenerative medicine."

[Michael Levin @drmichaellevin]

New #preprint - @BeneHartl @LPiolopez

https://t.co/OTC3cLq0BY

"Neural cellular automata: applications to biology and beyond classical AI"

[Michael Levin @drmichaellevin]

Final version of this paper with @AMPietak is now out:
https://t.co/oVZip6S3k1
"Harnessing the analog computing power of regulatory networks with the Regulatory Network Machine"

Abstract: gene regulatory networks (GRNs) are critically important for efforts in biomedicine and biotechnology. Here, we introduce the Regulatory Network Machine (RNM) framework, demonstrating how GRNs behave as analog computers capable of sophisticated information processing. Our RNM framework encapsulates: (1) a dissipative dynamic system with a focus on GRNs, (2) a set of inputs to the system, (3) system output states with identifiable relevance to biotechnological or biomedical objectives, and (4) Network Finite State Machines (NFSMs), which are maps detailing how the system changes equilibrium state in response to patterns of applied inputs. As an extension to attractor landscape analysis, the NFSMs map the sequential logic inherent in the GRN and, therefore, embody the “software-like” nature of the system, providing easy identification of specific applied interventions necessary to achieve desired, stable biological outcomes. We illustrate the use of our RNM framework in important biological examples, including in cancer renormalization.

[Michael Levin @drmichaellevin]

New paper with @BeneHartl : 'What does evolution make? Learning in living lineages and machines"
https://t.co/s4akXzdhrJ

Genes code for proteins, but what is the relationship between the genome and the large-scale form and function of organisms? What is a good formalism for thinking about what genomes actually do, that unlocks discovery of new plasticity of systemic outcomes in regenerative medicine and bioengineering contexts, as well as help understand how evolution operates on a reprogrammable (actually, agential) medium? What concepts from the fields of cognitive science, diverse intelligence, and computer science have relevance here?

Abstract: "Biology implements a multiscale competency architecture (MCA), where components competently navigate problem domains (e.g., metabolic, physiological, transcriptional, and anatomical). Biological subsystems continuously shape (hack) each other’s behavior, toward homeodynamic goal states emerging at new scales. The genome acts as a generative model, not a hardwired algorithm nor a blueprint, for species-specific form and function. A bowtie architecture enables evolutionary lessons of the past to be generalized into lineage memory engrams which are then actively decoded (interpreted) in ways appropriate to default or novel situations by the morphogenetic machinery. Fundamental symmetries across evolution, development, and behavior involve learning and creative problem-solving, which can be modeled by machine learning (ML) concepts such as autoencoders (AEs) and neural cellular automata (NCAs)."

A closely related and excellent paper by @WiringTheBrain and @CheneyLab :
https://t.co/ZFkoofLhGq

[Michael Levin @drmichaellevin]

Official version of this paper with @LPiolopez is out:

https://t.co/l4RwfOTIGw

Universal multilayer network embedding bioinformatics method, and validation data in frog model (relevant to cancer)

[Michael Levin @drmichaellevin]

Next up, @LPiolopez and a remarkable finding about #aging. Preprint here: https://t.co/lyUdFGX4L0
Atavistic Genetic Expression Dissociation (AGED) during aging: meta-phylostratigraphic evidence of cellular- and tissue-levels phylogenetic dissociation

Abstract:
"Aging is commonly attributed to accumulated damage, or evolved antagonistic genetic trade-offs, which lead to an accumulation of genetic damage, noise, or DNA methylation causing the misexpression of key genes necessary for longevity. We propose an atavistic dysregulation of gene expression at cellular and tissue-levels during aging, which frames aging as a gradual regression toward ancestral cellular states. Similar to the atavistic model of cancer, in which cells revert to unicellular-like behavior, aging may result from a progressive breakdown of coordinated morphogenetic control, leading organs and tissues to revert towards less integrated, ancient unicellular states. This view suggests that aging may involve a progressive reversal of the well-known ontogenetic tracing of prior phylogenetic embryonic characteristics. Moreover, as in cancer, aging could involve a loss of large-scale coordination, with different tissues reverting to ancient gene expression to different degrees. We tested this hypothesis using a meta-phylostratigraphic analysis to ask: do older human tissues express more ancient genes, and does the variance of transcriptional phylogenetic age across tissues increase with organismal age? We found: (1) An atavistic over-representation of differential expression in the most ancient genes for two multi-tissue aging databases covering skin, ovarian, immune, senescent and mesenchymal-senescent cells; (2) No atavistic over-representation of the differential genet expression during aging of brain cells and mesenchymal stem cells; and (3) overall age-dependent increase of heterogeneity in the direction of the phylogenetic position of tissues’ transcriptional profiles. Our analyses suggest that aging involves uncoordinated and tissue-specific phylogenetic changes in gene expression. Understanding aging as a structured, heterogenous atavistic process opens new avenues for rejuvenation, focusing on restoring multicellular coherence with respect to evolutionarily-youthful gene expression."

In other words, during aging, some tissues shift their gene expression toward more ancient genes, and, there arises a lack of concordance between body tissues with respect to the phylogenetic age of the genes they express. Thus, while I often talk about morphogenetic/cognitive systems dissociating and losing integration spatially, it appears that aging is a dissociative disorder with respect to time (evolutionary time). Lots more to do, but very exciting.