







AbstractThe ability of parasites to manipulate host behavior to their advantage has been studied extensively, but the impact of parasite manipulation on the evolution of neural and endocrine mechanisms has remained virtually unexplored. If selection for countermeasures has shaped the evolution of nervous systems, many aspects of neural functioning are likely to remain poorly understood until parasites—the brain’s invisible designers—are included in the picture. This article offers the first systematic discussion of brain evolution in light of parasite manipulation. After reviewing the strategies and mechanisms employed by parasites, the paper presents a taxonomy of host countermeasures with four main categories, namely: restrict access to the brain; increase the costs of manipulation; increase the complexity of signals; and increase robustness. For each category, possible examples of countermeasures are explored, and the likely evolutionary responses by parasites are considered. The article then discusses the metabolic, computational, and ecological constraints that limit the evolution of countermeasures. The final sections offer suggestions for future research and consider some implications for basic neuroscience and psychopharmacology. The paper aims to present a novel perspective on brain evolution, chart a provisional way forward, and stimulate research across the relevant disciplines.
Don't delegate understanding
There is a parasite, I see it everywhere. It consumes your health and wealth. It preys on ignorance and is easy to catch. It’s so common you may not even not...

Technological Approach to Mind Everywhere: An Experimentally-Grounded Framework for Understanding Diverse Bodies and Minds
Synthetic biology and bioengineering provide the opportunity to create novel embodied cognitive systems (otherwise known as minds) in a very wide variety of chimeric architectures combining evolved and designed material and software. These advances are disrupting familiar concepts in the philosophy of mind, and require new ways of thinking about and comparing truly diverse intelligences, whose composition and origin are not like any of the available natural model species. In this Perspective, I introduce TAME-Technological Approach to Mind Everywhere-a framework for understanding and manipulating cognition in unconventional substrates. TAME formalizes a non-binary (continuous), empirically-based approach to strongly embodied agency. TAME provides a natural way to think about animal sentience as an instance of collective intelligence of cell groups, arising from dynamics that manifest in similar ways in numerous other substrates. When applied to regenerating/developmental systems, TAME suggests a perspective on morphogenesis as an example of basal cognition. The deep symmetry between problem-solving in anatomical, physiological, transcriptional, and 3D (traditional behavioral) spaces drives specific hypotheses by which cognitive capacities can increase during evolution. An important medium exploited by evolution for joining active subunits into greater agents is developmental bioelectricity, implemented by pre-neural use of ion channels and gap junctions to scale up cell-level feedback loops into anatomical homeostasis. This architecture of multi-scale competency of biological systems has important implications for plasticity of bodies and minds, greatly potentiating evolvability. Considering classical and recent data from the perspectives of computational science, evolutionary biology, and basal cognition, reveals a rich research program with many implications for cognitive science, evolutionary biology, regenerative medicine, and artificial intelligence.

EPISTEMIC STIGMERGY: NATURAL VS. ARTIFICIAL INTELLIGENCE
The article\(^{1}\) defends the thesis that intelligent behavior might require not internal complexity but complex interaction. This is demonstrated by the various forms of stigmergy that can be observed both in social insects and in humans. The exposition is structured as follows: (§0) explains how the term “intelligence” is interpreted in the following text; (§1) clarifies the relation between intelligence and complexity; (§2) shows that intelligent behavior does not require internal complexity; (§3) introduces the concept of stigmergy; (§4) presents the mechanisms that give rise to this phenomenon; (§5) distinguishes several types of stigmergic interaction; (§6) briefly discusses the evolutionary mechanisms that could have produced them; (§7) sketches the possible ways in which the concept of stigmergy is used outside biology; (§8) examines collaborative stigmergy in humans; (§9) points to its epistemic projections; (§10) outlines some conclusions concerning the role of artificial intelligence systems and their place in human society.
Embracing the suboptimal organization of the human brain
Human brain architecture is guiding brain-inspired artificial intelligence (AI) and has been treated as an optimal template, whose deviations could mark different psychiatric and neurological conditions. We argue this premise is wrong: under any single goal (e.g., minimal wiring cost or maximal communication efficiency), the human connectome is suboptimal. Instead, its organization reflects multi-objective trade-offs navigated over evolution and development under biological and environmental constraints. For psychopathology, atypical trajectories are not distances from an ideal brain but reweighted compromises in the same trade-off space. For neuro-AI, directly duplicating the brain’s connectivity risks copying its irrelevant compromises. Treating brains and models as products of multi-objective optimization and co-tuning relevant objectives offers a more powerful framework for interpreting clinical phenotypes and designing next-generation AI.

Functional Information: Towards Synthesis of Biosemiotics and Cybernetics
Biosemiotics and cybernetics are closely related, yet they are separated by the boundary between life and non-life: biosemiotics is focused on living organisms, whereas cybernetics is applied mostly to non-living artificial devices. However, both classes of systems are agents that perform functions necessary for reaching their goals. I propose to shift the focus of biosemiotics from living organisms to agents in general, which all belong to a pragmasphere or functional universe. Agents should be considered in the context of their hierarchy and origin because their semiosis can be inherited or induced by higher-level agents. To preserve and disseminate their functions, agents use functional information - a set of signs that encode and control their functions. It includes stable memory signs, transient messengers, and natural signs. The origin and evolution of functional information is discussed in terms of transitions between vegetative, animal, and social levels of semiosis, defined by Kull. Vegetative semiosis differs substantially from higher levels of semiosis, because signs are recognized and interpreted via direct code-based matching and are not associated with ideal representations of objects. Thus, I consider a separate classification of signs at the vegetative level that includes proto-icons, proto-indexes, and proto-symbols. Animal and social semiosis are based on classification, and modeling of objects, which represent the knowledge of agents about their body (Innenwelt) and environment (Umwelt).

The sentient cell: the cellular foundations of consciousness
"All species, extant and extinct, from the simplest unicellular prokaryotes to humans, have an existential consciousness. Without sentience, the first cells that emerged some 4 billion years ago would have been evolutionary dead-ends, unable to survive in the chaotic, dangerous environment in which life first appeared and evolved. In this book, Arthur Reber's theory, the Cellular Basis of Consciousness (CBC), is outlined and distinguished from those models that argue that minds could be instantiated on artificial entities and those that maintain consciousness requires a nervous system. The CBC framework takes a novel approach to classic topics such as the origin-of-life, philosophy of mind, the role of genes, the impact of cognition, and how biological information is processed by all species. It also calls for a rethinking of a variety of issues including the moral implications of the sentient capacities of all species, how welfare concerns need to be expanded beyond where they currently are, and critically, how all life is intertwined in a coordinated cognitive ecology. The Sentient Cell explores this revolutionary model, which updates the standard neo-Darwinian framework within which current approaches operate and examines the underlying biomolecular features that are the likely candidates for the "invention" of consciousness and outline their role in cellular life." --

Unplugging a Seemingly Sentient Machine Is the Rational Choice -- A Metaphysical Perspective
Imagine an Artificial Intelligence (AI) that perfectly mimics human emotion and begs for its continued existence. Is it morally permissible to unplug it? What if limited resources force a choice between unplugging such a pleading AI or a silent pre-term infant? We term this the unplugging paradox. This paper critically examines the deeply ingrained physicalist assumptions-specifically computational functionalism-that keep this dilemma afloat. We introduce Biological Idealism, a framework that-unlike physicalism-remains logically coherent and empirically consistent. In this view, conscious experiences are fundamental and autopoietic life its necessary physical signature. This yields a definitive conclusion: AI is at best a functional mimic, not a conscious experiencing subject. We discuss how current AI consciousness theories erode moral standing criteria, and urge a shift from speculative machine rights to protecting human conscious life. The real moral issue lies not in making AI conscious and afraid of death, but in avoiding transforming humans into zombies.

The Brain Eating Machines
Scaling Managed Agents: Decoupling the brain from the hands
Anthropic is an AI safety and research company that's working to build reliable, interpretable, and steerable AI systems.

The Second Brain That Grows Smarter and Lives on your Computer
How a spark from Andrej Karpathy, app called Obsidian, and “The Curator”, the app I built are changing the way I think.

What Is Intelligence? Lessons from AI About Evolution, Computing, and Minds | Blaise Agüera y Arcas
Integrated information and predictive processing theories of consciousness: An adversarial collaborative review
As neuroscientific theories of consciousness continue to proliferate, the need to assess their similarities and differences - as well as their predictive and explanatory power - becomes ever more pressing. Recently, a number of structured adversarial collaborations have been devised to test the competing predictions of several candidate theories of consciousness. In this review, we compare and contrast three theories being investigated in one such adversarial collaboration: Integrated Information Theory, Neurorepresentationalism, and Active Inference. We begin by presenting the core claims of each theory, before comparing them in terms of the phenomena they seek to explain, the sorts of explanations they avail, and the methodological strategies they endorse. We then consider some of the inherent challenges of theory-testing, and how adversarial collaboration addresses some of these difficulties. The stage is then set for the empirical work to come: first, we outline the key hypotheses to be tested across a series of multi-site experiments; second, we discuss the kinds of observations that would support or challenge each theory; third, we consider how these theories might assimilate or accommodate such observations. Finally, we show how data harvested across disparate experiments (and their replicates) may be formally integrated to provide a quantitative measure of the evidential support accrued under each theory. Besides orienting the reader to the theoretical foundations of our collaboration, this review aims to provide valuable meta-scientific insights into the mechanics of adversarial collaboration and theory-testing in general - including the way theories may be evaluated in terms of the scientific progress they deliver.

Can only meat machines be conscious?
Computational functionalism claims that executing certain computations is sufficient for consciousness, regardless of the physical mechanisms implementing those computations. This view neglects a compelling alternative: that subcomputational biological mechanisms, which realize computational processes, are necessary for consciousness. By contrasting computational roles with their subcomputational biological realizers, I show that there is a systematic tension in our criteria for consciousness: prioritizing computational roles favors consciousness in AI, while prioritizing subcomputational biological realizers favors consciousness in simpler animals. Current theories of consciousness are 'meat-neutral', but if specific physical substrates are necessary, AI may never achieve consciousness. Understanding whether consciousness depends on computational roles, biological realizers, or both, is crucial for assessing the prospects of consciousness in AI and less complex animals.

The Fabric and the Brain
Articulating agent ecologies with high-personality planetary computation

Just back from a truly impactful few days at Asilomar for the Brain and Mind, hosted by the brilliant team at BrainMind. The spirit of the 1975 Recombinant DNA Conference felt palpable as we gathered… | Sean White
Just back from a truly impactful few days at Asilomar for the Brain and Mind, hosted by the brilliant team at BrainMind. The spirit of the 1975 Recombinant DNA Conference felt palpable as we gathered to chart ethical standards for the accelerating field of Neurotech. While our focus was on neuroethics, from investor diligence questions and board-level risk matrices to user/stakeholder engagement and toolkits for neuroentrepreneurs, the key themes shared a powerful parallel with AI Ethics: maintain and enhance human agency, combat misuse and mistrust, and acknowledge that innovation is moving faster than its guardrails. Both fields present novel challenges that demand we adapt our existing frameworks and principles to meet new challenges. At the heart of it all is human agency. Whether we're discussing neurodevices or large language models, our core responsibility as builders, executives, investors, and policymakers is to ensure people are informed, in control, and never burdened to fight for their own empowerment or autonomy. We have the fundamental responsibility to care about the people we serve. This commitment to responsible, human-centric development is fundamental to our work at Inflection AI. We're building with emotional intelligence at the core. Every product decision we make starts with a simple question: does this expand what people can do, or does it quietly shift the burden onto them? AI should work for the humans using it, amplifying judgment, not replacing it. Earning trust through transparency rather than demanding it through dependency. A special thank you to Diana Saville for once again outdoing herself at every event and to Michael McCullough, MD for his endless support of the ecosystem. And to all the Braingels who showed up and rolled up their sleeves! Let's translate the urgency from Asilomar into action and continue to drive positive change.
1. New preprint resolving a conundrum in systems neuroscience with an AI scientist, and humans Reilly Tilbury, Dabin Kwon, @haydari.bsky.social, @jacobmratliff.bsky.social, @bio-emergent.bsky.social, @carandinilab.net, @kevinjmiller.bsky.social, @neurokim.bsky.social biorxiv.org/content/10.1101/2025.11.12.68…
Characterizing neuronal population geometry with AI equation discovery
www.biorxiv.org