TTS

Brains and where else? Mapping theories of consciousness to unconventional embodiments

Nicolas Rouleau${}^{1,2}$ and Michael Levin${}^{2,3}$

${}^1$Department of Health Sciences, Wilfrid Laurier University, Waterloo, Ontario, Canada
${}^2$Allen Discovery Center, Tufts University, Medford, MA, USA
${}^3$Wyss Institute for Biologically Inspired Engineering, Harvard University, Boston, MA, USA

NR, [0000-0003-4592-6280](https://orcid.org/0000-0003-4592-6280); ML, [0000-0001-7292-8084](https://orcid.org/0000-0001-7292-8084)

GRAY

It is assumed that a useful theory of consciousness (ToC)T o C will explain why consciousness is associated with brains. However, the findings of evolutionary biology, developmental bioelectricity and synthetic bioengineering reveal ancient pre-neural roots of many mechanisms and algorithms occurring in brains: minds may have preceded brains. Most work in the emerging field of diverse intelligence emphasizes externally observable problem-solving competencies in unconventional media, such as cells, tissues and life-technology chimeras. Here, we inquire about the implications of these developments for ToCstheories of consciousness. Specifically, we analyse popular current ToCstheories of consciousness to ask: What features of each theory specifically pick out brains as a privileged substrate of inner perspective, or do the features emphasized by the theory occur elsewhere? We find that the operations and functional principles of most ToCstheories of consciousness are not confined to neural substrates, and that the focus on brains is more driven by convention than by the specific content of existing ToCstheories. Encouragingly, several contemporary theorists have made explicit efforts to apply their theories to synthetic systems in light of recent technological developments in artificial intelligence and organoid bioengineering. We suggest that the science of consciousness should remain open to minds in unconventional embodiments.

This article is part of the theme issue ‘World models in natural and artificial intelligence’.

**Opinion piece**

Cite this article: Rouleau N, Levin M. 2026 Brains and where else? Mapping theories of consciousness to unconventional embodiments. Phil. Trans. R. Soc. A 384: 20250082. https://doi.org/10.1098/rsta.2025.0082

Received: 25 April 2025
Accepted: 17 September 2025

One contribution of 18 to a theme issue ‘World models in natural and artificial intelligence’.

Subject Areas:
artificial intelligence, robotics, software, systems theory

Keywords:
consciousness, aneural cognition, functionalism, organizational invariance, unconventional minds

Authors for correspondence:
Nicolas Rouleau
e-mail: nrouleau@wlu.ca
Michael Levin
e-mail: michael.levin@tufts.edu

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© 2026 The Authors. Published by the Royal Society under the terms of the Creative Commons Attribution License http://creativecommons.org/licenses/by/4.0/, which permits unrestricted use, provided the original author and source are credited.

royalsocietypublishing.org/rsta

1. Introduction

What processes or algorithms underlie the ability of certain physical objects, such as living bodies, to form memories, implement decision-making, have an inner perspective with preferences and navigate their environment in a goal-directed manner? This question is crucial to our understanding of ourselves, the development of ethics and social systems and the status of hybrid and fully synthetic artificial intelligence (AI). A number of formalisms, including that of Turing [1] and later, the connectionist paradigm [2–7], have attempted to delineate what it is that confers mind within a given embodiment. In all cases, however, it was assumed that the formalisms’ dynamics describe events in brains. What would have happened if, instead of touting the functional capacities of brains, the biologists came to pioneers in the field of AI, such as McCulloch [3], Pitts, Papert, Rosenblatt, etc. and said: ‘we were wrong, the human mind is in the liver’? Would they have had to modify their models, or shrug it off as irrelevant to their efforts? What is actually ‘neural’ about artificial neural networks, used to attempt to understand minds and build AI? Specifically, what aspects of neuroscience-inspired formalisms are actually tied to neurons per se, as opposed to other cell types?

This seems like an odd question—surely neurons are unique, and there must be a reason why minds associate with brains? This assumption, which permeates discussions of AI and philosophy of mind, is becoming increasingly difficult to hold for several reasons. First, evolutionary developmental biology shows how brains evolved gradually from other cell types. Indeed, the molecular mechanisms that set up the bioelectric networks of the brain are ancient—existing in all cells of the body and having their origin in bacterial biofilms [8–11]. Phylogenetically, ancient traits of all kinds are carried forward and even implemented by new substrates (i.e. degeneracy)—so, why not the mechanisms underlying mindedness? Second, memory, creative problem-solving, decision-making and numerous other aspects of active agency have now been observed in cells, tissues, slime moulds and even small molecular networks [12–16]. Advances in biophysics, cell biology and behavioural science are revealing deep evolutionary commonalities between the mechanisms and algorithms of neuroscience and other fields such as developmental biology, for example, in the study of cell groups as a collective intelligence that navigates anatomical space [17,18].

Thus, the emerging field of diverse intelligence reveals that the focus on brains, and on the readily observable movement of organism-sized (cm, m) objects at behavioural time scales (ms, s) through the three-dimensional world, is a result of our evolutionary firmware. Efforts to expand from this neuro- and anthropocentric myopia are underway via research on the problem-solving competencies of a wide range of living and synthetic agents, which is helping to erode our limited evolutionary firmware for visualizing minds in unconventional embodiments [19]. To date, however, all of the work in this field has focused on externally observable behaviour—problem-solving, or the ‘easy’ problem of consciousness [20]. What of the hard problem—how to explain the inner perspective and elucidate its relationship to the brain? That current theories of consciousness (ToCs; [21,22])T o Cs focus on correlates, markers, metrics, physical interactions, objective referents and other events with which to infer conscious states rather than pointing directly at subjectivity reflects a long-standing habit in the field of defining consciousness in terms that presuppose what it sets out to explain. But if that is the standard when evaluating consciousness in humans, the same standard should be applied to all systems; neglecting to do so a priori is tantamount to begging the question.

Here, we explore the state of consciousness research with a focus on ToCs and inquire about the implications of recent breakthroughs in biology for theories that make a claim about what is necessary and/or sufficient for consciousness. Specifically, we analyse popular current ToCs to ask: What features of the theory specifically pick out brains as a privileged substrate of inner perspective, or do the features emphasized by each theory occur elsewhere, in natural bodies and perhaps even in the world of engineering? We find that most ToCs rely on functional

principles that are not specific to neuronal networks, which means that their claims about consciousness should apply to a wide range of unconventional substrates. We find few specifics about why neuronal assemblies, in particular, would be an exclusive substrate for consciousness and suggest that the focus on brains is more driven by convention and understandable limitations of imagination than by any specific content of existing ToCs. Thus, it is interesting to explore the relationships of various ToCs with the nervous system per se and the consequences of taking seriously the features they emphasize when they occur outside of brains.

1.1. Theories of consciousness as tools to counteract pervasive mind-blindness

Specific ToCs offer long-awaited explanatory and predictive power amid a history of confusion about the nature of experience. By what standard can a ToC be assessed as useful? Insofar as it can reliably point to subjects in the world, a ToC accomplishes its most basic function. But what if the theory can only reliably point to a particular type of subject? The validity of any theory that purports to explain how and where experience manifests is impacted not only by its positive identifications of mind but also by the number of true minds that it leaves unidentified. Though practical distinctions have always been made to classify the contents of experience, there is yet no consensus definition of consciousness or ToC that accounts for its mechanisms. We usually have no problem being epistemically confident about our own inner perspective. However, the existence of other minds with private thoughts and feelings may be fundamentally unknowable [23–26]. Still, humans share a robust intuition that we live among other minds in a shared environment [27]. That others speak, gesture, respond and emote in ways that mirror our own behavioural correlates of consciousness reinforces a theory of mind that underlies the social and moral systems humans have created and refined over hundreds of thousands of years [27], and the ancient biological firmware that tuned our agency detectors for specific kinds of behaviours in visible space. Whether it reflects reality or not, humans engaged in world modelling infer the existence of other embodied minds within their environments, and this leap of faith (and its attendant limitations) is a normal feature of human psychology.

Mind-blindness—or a failure to form a theory of mind in the presence of other humans—is a defining characteristic of some common neuropathologies but is relatively rare in the general population [28]. Indeed, most humans routinely infer the presence of other minds to inform their social behaviour and ethics. However, we suggest that all humans are insensitive to a wide range of unconventional minds, without sensing any kind of deficit, in the same way that we are insensitive to huge swaths of the electromagnetic spectrum without feeling impaired or appearing as such to other humans. If our default cognitive apparatus was significantly mind-blind to major categories of unconventional beings, we would not know about it without developing tools in the same way that physics and a useful theory of electromagnetic waves opened our awareness to the existence of X-rays, radio waves and other signals that our default configuration cannot perceive. This analogy also works because light and X-rays simply do not seem like what happens when you wave a magnet up and down—on a superficial level, they appear quite different indeed. And yet, a rigorous formalism allowed us to overcome our limited intuitions and see electromagnetics in all of its guises. Is there a reason to hypothesize that the same situation awaits us with respect to the space of possible minds?

Our apparent inability to model worlds full of unconventional minds could indicate that such a capacity was orthogonal to fitness outcomes throughout our evolutionary history. However, it is more likely that mind-blindness confers fitness advantages in the same way that other distortions of perception are thought to have increased survival and reproduction relative to unfiltered windows to reality [29,30]. Consider the example of predation. While searching for and capturing prey may depend on an ability to predict the actions of prey (which could benefit from a theory of mind), killing and eating prey (in many cases, while the organism is alive and struggling for survival) are unlikely to be advantaged by an awareness of other minds

and their analogous subjective states. Being aware of another animal’s pain, fear, suffering or distress of any kind in a way that registers as a reflection of one’s own emotional state is unlikely to benefit predators, whose survival is dependent on regularly killing and eating other organisms. Therefore, some minds may be perceptually siloed from others by virtue of their competitive advantage. On the other hand, it is conceivable that some minds were not shaped by similar selective pressures and readily engage in world modelling that includes or even privileges awareness of other embodied minds in the environment. In any case, we propose that regardless of the origins and pressures that shaped our limitations with respect to modelling the full spectrum of agency in our world (and others’ worlds), we now have the opportunity (and responsibility) to go beyond those native limitations as we have surpassed so many others.

Developmental biology and evolutionary theory emphasize the continuity of conserved mechanisms and algorithms spanning slowly and gradually from single cells (such as microbes and fertilized eggs) to adult metacognitive humans and the gradual modification of generic cells and cell networks into neurons (figure 1). The gradual self-construction of the body suggests the natural possibility of the gradual appearance of consciousness (and thus its presence, in degrees, in substrates different from an adult brainy animal), as perhaps reflected in Turing’s interest in synthetic intelligence and the spontaneous patterning of embryonic morphogens [1,41]. In addition, recent advances in bioengineering, synthetic biological intelligence, AI, brain–computer interfaces and robotics have fundamentally challenged our mind-inferencing strategies. The interoperability of life with engineered components is revealing a wide option space of hybrid beings that do not fit into classic life/machine categories ([42]; figure 2). Thus, whether or not the behaviour patterns of ‘artificial’ and hybrid systems reveal the presence of an experiencing subject has become a topic of great interest to many. ToCs, as principled theories for where one can expect inner perspective, promise to enable technologies to reveal heretofore unrecognized vistas—like tele-spectroscopy, which revealed familiar earthly elements in then-unexpected locations: celestial objects. To overcome the limitations of a human-centred theory of mind and increase true positive identifications of unconventional manifestations of consciousness in the environment, ToCs must be sufficiently universalizable to account for other minds. Are current ToCs formulated with other minds, well, in mind?

1.2. Why neural correlates fall short as consciousness criteria

Consciousness cannot be directly measured; therefore, correlates have been used as indirect signs of an underlying mind in the same way that the presence of a black hole is inferred on the basis of how light is bent or ‘lensed’ by distortions of space–time. Many contemporary ToCs refer to ‘neural correlates’ of consciousness (NCCs), which are a set of conserved relationships between human brain structure–function and self-reported experiences [48]. Why ‘neural correlates’ as opposed to, simply, ‘correlates’? Following localized brain lesions, neural stimulation or the use of psychoactive compounds, humans report highly conserved experiential phenomena that map onto common brain regions as revealed by neuroimaging [48]. While its flow may be interrupted by sleep or altered by drugs, anaesthetics, rituals and environmental forces, the evidence indicates that consciousness is a shared feature of human brains with stereotyped structure–function correlates. Because brain morphology is highly conserved (i.e. most brains display the same gyri, sulci, nuclei, tracts, circuits, networks, etc.), NCCs can be generalized across members of the human species, allowing us to overcome weaker forms of mind-blindness in clinical settings. Until the development of brain imaging, immobile and seemingly unresponsive coma patients were lumped into the category of non-conscious systems with most organisms, robots and the deceased; however, with NCCs, new degrees of distinction could be made, including the confirmation of a minimally conscious state [49–52]. NCCs predict the existence of recondite minds on the basis of neural activations alone if the same activations were associated with the reported experiences of others. This mind-detecting strategy, termed

Figure 1. Self-assembly of conscious beings from the agential material of life. (A) Each of us is the product of a transformational process (embryogenesis) that leads from a quiescent oocyte well encompassed by the laws of chemistry to a complex meta-cognitive agent amenable to behavioural science or even psychoanalysis. This journey across the ‘Cartesian cut’ is slow and gradual, with no place for a bright line during which physics suddenly becomes mind. Generic cells become neurons, some electrophysiological networks speed up to become nervous systems and motility in three-dimensional space appears, whereas before there was only navigation of metabolic, gene expression and anatomical spaces. (B) Aspects of cognitive function appear long before neurons and are universal, not even requiring cell networks or whole cells. For example, modelling and wet lab studies are beginning to suggest that unicellular organisms [31,32], chemical networks within all cells and a wide range of materials may be capable of several different kinds of learning [32–36] and even probabilistic inference [37,38]. (C) Biological material in general has problem-solving competencies and agents at every level of organization, from the active matter within cells to tissues and organs navigating physiological spaces and learning from experience [13,39]. Panel A taken with permission from [40]. Panel B taken with permission from [34]. Panel C taken with permission from [17]. All images courtesy of Jeremy Guay of Peregrine Creative.

‘reverse inference’ [53], is a practical solution to mind-blindness when the potential subject in question is a human with a brain.

Unfortunately, any movement across the phylogenetic tree decreases the predictive power of reverse inference because NCCs are fundamentally correlates and can only be used to infer consciousness in precisely the same way that behaviours motivate the same inferences. If the associations in question are non-generalizable, such as involving very specific nervous systems with defined organizations, the logic of reverse inference breaks down. While many ToCs have highlighted the relevance of NCCs, their poor generalization to non-human subjects limits their utility. How would an NCC-dependent ToC map onto the distributed nervous system of a jellyfish or the ganglia of a mollusc? What can current ToCs offer in terms of predicting a capacity for experience when comparing three-layered and six-layered cortices or their intermediates? Unless a ToC can account for differences in neural organization, it will return the same predictive errors that human intuitions commit when assessing the mental status of anything other than a human. Some authors have suggested the use of perturbational complexity as a measure of consciousness, which, despite its focus on the responses of neural tissues, has the potential to transcend a historical reliance on specific NCCs because, in principle, other systems can display brain-independent perturbational markers that predict conscious experience [54,55].

Despite the long-standing absence of any direct measure of consciousness and strong philosophical reasons to doubt its existence in others, humans often extend a theory of mind to infer non-human animal sentience [56]. Interestingly, the degree to which a non-human animal shares superficial, human-like characteristics is predictive of our willingness to infer

Figure 2. The continuum of the natural and the engineered. (A) The ‘human’ that features so prominently in conventional philosophy of mind is at the centre of two continua. First (vertical) is the set of gradual changes on the evolutionary and developmental time scale that connects us to single cells and subcellular matter before that. The sense of consciousness we attribute to humans (represented by the agential glow) must, given the facts of developmental and evolutionary biology, be explained with respect to its degree and kind in closely connected forms. The continuity and transformation of mental properties from very minimal origins is the null hypothesis, and theories proposing the appearance of binary categories (‘is it conscious or isn’t it’) would need to argue convincingly and explicitly for mechanisms of emergent phase transitions. Second (horizontal) is a spectrum of continuous change that can be (and is being) implemented, both biologically and technologically, resulting in a wide array of composite, chimeric beings that are not easily categorized within or outside of ‘human’ minds. This means that our theories of consciousness should not be human-centred but rather encompass a wide and continuous space of minds [43–47]. (B) Another key feature of biological organization is that it can be readily hybridized with engineered, designed components at every level. This interoperability of life with novel structures means that discussions of consciousness cannot focus on ‘life versus machine’ but must accommodate a rich space of chimeric forms with features not explainable by evolutionary history or selection pressures. Panel B taken with permission from [17]. All images courtesy of Jeremy Guay of Peregrine Creative.

subjectivity on the basis of their behaviours [57,58]. Once again, reverse inference is used to bridge the epistemic gap (i.e. analogous behaviours and observable traits as predictors of mind). Prior to a scientific study of animal consciousness, moral considerations were granted to many non-human animal species, and most people are quite happy to assume that their pets lead rich, experiential lives with felt states of pleasure and pain. In many countries, non-human animal species, such as dolphins and chimpanzees, enjoy personhood status [59,60] that sets them apart from other living systems, including plants, insects and microorganisms—which together constitute over 99% of Earth’s biomass [61]. In other words, less than 1% of living systems on the planet are granted special status and consideration over the vast majority due to their presumed subjectivity, even though the rest have long been known to exhibit different degrees of learning, decision-making, predictive capacity, etc. [13,62–65]. Notably, much less than 1% of living systems on Earth possess a nervous system. If even a minority subset of aneural life is conscious—perhaps a single plant or animal species—the NCC standard will fail to account for their experiences, generating false negative errors wherever it is applied.

While recent developments in synthetic biological intelligence and AI research have accelerated discussion around the topic of unconventional minds, the emergence of neural-robotic hybrids in the late twentieth century represented a major branching point in the conversation. That cultured neural networks could be coupled with robotic or virtual ‘bodies’ to solve real-world problems challenged long-standing dichotomies between the living and

non-living or the agential and automatic [66–68]. It was quickly realized that disembodied brains were dysfunctional but could be normalized with stochastic inputs or response-contingent feedback [69–71]. Now, there is evidence to suggest that cultured neural networks in closed-loop feedback systems can optimize their outputs towards many types of defined goal states without external programming [72]. Importantly, these displays of self-organized problem-solving are achieved without specialized, genetically encoded brain circuits. That is, embodied cultured networks demonstrated that, fundamentally, there is no intrinsic, universal value to any particular tract system, nucleus or circuit outside of its default context. Rather, a sufficiently plastic neural network can be shaped to accomplish any number of tasks. Once considered exclusive to human brains, cognitive functions such as learning, attention and decision-making have, over time, been incrementally extended to living and non-living systems alike. While it is possible that any one or perhaps all of these features of cognition could be displayed without an experiential correlate, the stakes are high—not knowing whether a physical object with which you are engaged is conscious is an ethical risk. This is especially relevant now that a much wider variety of beings—biobots [73–76], cyborgs [77–83] and minimal active matter systems [84–88]—are coming online and beginning to be bioengineered. ToCs will need to be applied to an ever-increasing number of organizationally unique systems with potential minds [17,42,89].

ToCs are important. Whether or not they hold construct validity (i.e. how well the ToC not just predicts the presence of a subject but actually describes true features or mechanisms of consciousness), they enable us to make meaningful distinctions that inform decisions related to lifestyle, ethics, public policy and law. Frameworks must now be developed to identify unfamiliar minds in unconventional spaces that betray long-standing neurocentric assumptions [17,65,90]. Here, we survey contemporary ToCs and explore their suitability to identify other kinds of minds in diverse environments. How many of them are actually neuron-specific? While many ToCs have already adopted a panpsychist, functionalist or universalized approach, some still focus exclusively on the brain, even though nothing about their ‘secret sauce’ is actually unique to neurons.

2. Neural tissues as non-exclusive specialists of cognitive function

Because ToCs that reference NCCs or any specific neurobiological details will likely fail to generate a true positive prediction of unconventional minds, the role of the brain within the cognitive landscape must be revisited. Neurons—and specifically, pyramidal cells—were once described by Ramón y Cajal as ‘the butterflies of the soul’. The implication, of course, was that neural cells conferred the properties of minds, which remains a central assumption of modern neuroscience. However, there is no single feature of the neuron that is not also displayed by some other cell, living system, inorganic material or natural process (figure 3). Whether it is a capacity for long-range signalling, cell shape plasticity, chemical communication, electrotonic coupling, electromagnetic sensing, membrane polarization, chemotaxis, galvanotaxis, ephaptic coupling or networking, the neuron holds no exclusive capacity or function [93–95]. While the label ‘neuron’ is most commonly applied to cells with the ability to form very long point-to-point connections, many other cell types possess degrees of this architecture via tunnelling nanotubes and other structures (reviewed in [96]), including pigment cells that can make long projections, reaching a significant proportion of the way across the entire body in tadpoles [97].

Many living systems display electrochemical patterns that are homologous to those of neurons, including the electromagnetic fields that have been hypothesized to be important for consciousness [98–104]. Most bodily cells regulate membrane-bound ion channels to maintain a polarized electrical state; however, neurons display notably hyperpolarized resting potentials (−70 mV)minus seventy millivolts. Cardiomyocytes, which are similarly hyperpolarized at rest (−90 mV)minus ninety millivolts, generate spontaneous depolarizations or ‘action potentials’ [105] with refractory periods and other dynamics that are similar but not identical to those of neurons (and participate in a

Figure 3. Strong symmetry between neural and non-neural cognitive substrate. (A) In the nervous system, the hardware consists of a network of cells connected by chemical and electrical synapses (i); the goal of neural decoding (ii) is to read the physiological states of the brain ((iii) bioelectric imaging of a living vertebrate brain) and decode them to infer the cognitive content of the mind embodied by this network—to be able to extract the memories, goals, preferences and conscious state. (B) The powerful properties of bioelectric networks that enable memory, re-entrant network architectures and integration of information across space and time are not unique to neurons: all cells in the body have ion channels for generating spatio-temporal patterns of resting potential and gap junctions (electrical synapses) for shaping those patterns in light of ongoing processing (i); precisely the same tools, ranging from optogenetics to computational pipelines to crack the somatic bioelectric code (ii), are being used to decode the goal states, memories and navigational behaviours of bioelectric patterns ((iii) voltage sensing dye showing dynamic gradients in the early frog embryo) during decision-making and problem-solving in the anatomical morphospace. Panels A(i), B(i) and B(iii) taken with permission from [40]. Panels A(ii), B(ii) taken with permission from [91]. Panel A(iii) taken with permission from [92]. Image in panel B(iii) is by Dany Adams, Levin lab. All other images are courtesy of Jeremy Guay of Peregrine Creative.

phenomenon known as cardiac memory [106,107]). Immune cells can be sensitized, display learnt responses and encode long-term memories reflective of a history of exposure to specific pathogens [108], just like cells of the nervous system form long-term memories reflective of a history of sensory inputs. Neurotransmitters, such as glutamate and serotonin, are expressed throughout the body, outside the brain [109] and by many plant species as chemical signals for cellular communication [110]. Incidentally, plants display anticipatory responses and even game-theoretic decision-making capabilities that weigh the availability of resources with the kin status of neighbouring organisms, determining the expression of competitive or cooperative actions [111]. Unsurprisingly, some authors have called for a more inclusive definition of ‘nervous system’ that captures a spectrum of signal generation, transmission and processing in multicellular systems [112]. Paramecia [32,36,113] and slime moulds [114–116] can be conditioned and even solve problems without nervous tissues. We previously demonstrated that non-associative learning, such as habituation, is a commonplace function that is not dependent on any specific biological substrate or cell type [117,118]. Several authors have since suggested that learning is a universal property shared by cells, generally [14,15,119–123].

Dynamical properties of neurons are also displayed by simple molecular interactions at sub-cellular scales [124]. Indeed, phospholipid membranes alone display memcapacitive properties that recapitulate long-term potentiation without cells or synapses [125]. Water at an interface generates negative potential differences (voltage) within the range of resting membrane potentials (−100 mV)minus one hundred millivolts that can be modified by the addition of physiological ions

and detected hundreds of microns away from the surface [126]. Microtubules and their special properties have been suggested to be critical for consciousness [127–130], but cytoskeletal structures, such as microtubules, are present in all cells and play an important role in cellular and multicellular decision-making and collective behaviour [131–134]. Moreover, microtubules in a dish spontaneously align with and migrate along electric fields [135,136] and polymerize as branched networks with dendrite-like arbours. Incidentally, branching patterns of neurites, plants and blood vessels conform to the same scaling laws [137–139]. Even inorganic substrates, such as iron bars, are subject to conditioned hysteresis responses [140], and silver nanowires display self-assembling properties in the presence of electric current that optimize patterning with properties of learning and memory [141]. Interestingly, the current densities, firing frequencies, backpropagation responses and saltatory-conductive properties of neurons are also displayed by lightning strikes between the Earth’s surface and its atmosphere [142].

Neither the composition nor the dynamics of neurons is sufficiently unique to justify their special status as mind generators. Either individual cell properties are insufficient or many types of simple systems are similarly capable of generating conscious states. The third possibility is that brains deserve exclusive status because of their connective properties, local circuitry and network architectures. It is often suggested that structural complexity is what sets brains apart from other systems. However, contrary to popular assumption, a network architecture with sparse rather than dense connectivity is likely to specialize brains as implementers of cognition [143]. Notably, feedforward networks are unlikely to generate consciousness [52]. Feedback mechanisms, including reverberation by re-entrant circuits, are thought to be requirements for consciousness [144,145]. From a functionalist perspective, the organizational principles are more relevant than the substrates, and neural tissues represent one of many possible ways to implement cognitive functions by organizing matter into structured networks that transduce, process and transmit patterned energy as information. With many natural and synthetic examples of re-entry, feedback, network sparsity and plasticity outside the nervous system, there is good reason to doubt that brains occupy a privileged position over other systems with analogous organizational features. Here, we examine several contemporary frameworks from a functionalist perspective, with the aim of universalizing ToCs to interact with unconventional substrates and scales.

3. Theories of consciousness to map diverse embodied minds

A universalizable ToC should be substrate-independent, scale-invariant and organization-invariant [20], with the implication that mind is multiply realizable [89,146]. Unfortunately, when the properties of cognitive systems are divorced from their biological substrates, it can be difficult to know where to apply inferencing strategies and deeply unintuitive questions arise: what does it mean to be conscious in spaces other than the three-dimensional space at human spatio-temporal scales? Beyond the neural variety, what kinds of correlative phenomena can reliably serve as indirect measures of consciousness? What kinds of perturbations or physical interactions can reliably induce changes within a system that indicate the likely presence of a mind? Without the grounding of a testable ToC, little progress can be made. As an initial step towards mapping minds in unconventional spaces, we reviewed prominent theories of consciousness as recently selected by Seth & Bayne [21]Seth and Bayne and substituted neurocentric language with aneurocentric or generic terms. Expanded, aneurocentric versions of the primary claims of each theory were then constructed with language reflecting inclusion of different substrates, scales and organizations (see table 1). Common terms such as ‘sensation’ or ‘sensory’ were replaced with generic afferents such as ‘input’. Likewise, terms such as ‘motor’ were replaced with generic efferents, such as ‘output’. Similarly, terms such as ‘brain’ or ‘neuron’ were replaced with generic terms for potential loci of consciousness, including ‘system’ or ‘processor’, which we consider potentially interchangeable with ‘cell’, ‘core’, ‘hub’ and/or ‘node’, depending on the context of the specific ToC.

Table 1. Aneurocentric formulations of prominent theories of consciousness. The table contains the main ToCs (taken after [21]prior work); italics indicate the words that were generalized to show how the theory applies beyond brains. In many cases, no changes needed to be made. This illustrates how many ToCs are actually not about brains specifically but call out aspects that are relevant to diverse cells, systems and collectives.

theory	primary claim		references
active inference	original formulations (verbatim from [21])	consciousness depends on temporally and counterfactually deep inference about self-generated actions	[147,148]
	substitutions	none
	expanded aneurocentric formulation	consciousness arises from an embodied system’s continuous predictions about inputs, adjusting internal states and outputs based on prediction errors to minimize differences between expected and actual inputs
attention schema theory	original formulation	consciousness depends on a neurally encoded model of the control of attention	[149]
	substitutions	neurally $\to$ information-processing system
	expanded aneurocentric formulation	consciousness arises from an information-processing system assigning high degrees of certainty about the claim that the system itself contains an attention schema or subject
attended intermediate representation theory	original formulation	consciousness depends on the attentional amplification of intermediate-level representations	[150,151]
	substitutions	none
	expanded aneurocentric formulation	consciousness arises when intermediate-level or partially processed information becomes amplified by attentional resources and can enter working memory
beast machine theory	original formulation	consciousness is grounded in allostatic control-oriented predictive inference	[152–154]
	substitutions	none
	expanded aneurocentric formulation	consciousness is the effect of combining a subjective frame, or internal reference point generated by constantly updated representations of internal states, with perceptual content evoked by external stimuli
dendritic integration theory	original formulation	consciousness depends on integration of top-down and bottom-up signalling at a cellular level	[155]
	substitutions	cellular $\to$ processor
	expanded aneurocentric formulation	consciousness depends on a coupling between bottom-up and top-down processing that generates a reverberating or looped function
dynamic core theory	original formulation	consciousness depends on a functional cluster of neural activity combining high levels of dynamical integration and differentiation	[156]

(Continued.)

Table 1. (Continued.)

theory	primary claim	references
	substitutions	neural $\to$ processor
	expanded aneurocentric formulation	consciousness arises from an integrated cluster of high-complexity re-entrant processors, or a compositionally dynamic ‘core’, within an information-processing system that is much more strongly interactive with itself than with other parts of the system
electromagnetic field theory	original formulation	consciousness is identical to physically integrated, and causally active, information encoded in the brain’s global electromagnetic field
	substitutions	brain $\to$ information-processor
	expanded aneurocentric formulation	consciousness depends on information-processing activities by processors interacting with the complex interference patterns of time-varying electromagnetic field oscillations
global workspace theories (GWTs)	original formulation	consciousness depends on ignition and broadcast within a neuronal global workspace where frontoparietal cortical regions play a central, hub-like role
	substitutions	neuronal $\to$ information-processing system frontal/parietal cortical regions $\to$ processors
	expanded aneurocentric formulation	consciousness arises from the attention-gated integration of information within an exclusive global workspace or ‘hub’ that uses working memory and can selectively broadcast to multiple processors simultaneously that are within the system but outside of the hub
higher order theory (HOT)	original formulation	consciousness depends on meta-representations of lower order mental states
	substitutions	mental states $\to$ states
	expanded aneurocentric formulation	consciousness is the higher-order, meta-representational monitoring of the processing activities associated with lower-order states
information closure theory	original formulation	consciousness depends on non-trivial information closure with respect to an environment at particular coarse-grained scales
	substitutions	none
	expanded aneurocentric formulation	consciousness is a process $Y$ that forms information closure with a stochastic process $X$ of which it is a coarse-grained product
integrated information theory (IIT)	original formulation	consciousness is identical to the cause–effect structure of a physical substrate that specifies a maximum of irreducible integrated information

(Continued.)

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Table 1. (Continued.)

theory	primary claim		references
	substitutions	none
	expanded aneurocentric formulation	consciousness corresponds to the level of integrated information within a system, quantified by a measure ($\varphi$) where higher integration indicates richer, more coherent experiences
local recurrency	original formulation	consciousness depends on local recurrent or re-entrant cortical processing and promotes learning	[167,168]
	substitutions	cortical $\to$ processor
	expanded aneurocentric formulation	consciousness arises from recurrent or re-entrant feedback at points of interaction between higher and lower level processors
multiple drafts model	original formulation	consciousness depends on multiple (potentially inconsistent) representations rather than a single, unified representation that is available to a central system	[169]
	substitutions	none
	expanded aneurocentric formulation	consciousness consists of highly parallelized, multi-track processes of informational interpretation and elaboration with continuous editorial revision that are not represented as unified narratives
neural Darwinism	original formulation	consciousness depends on re-entrant interactions reflecting a history of value-dependent learning events shaped by selectionist principles	[170,171]
	substitutions	none
	expanded aneurocentric formulation	consciousness is a re-entrant interaction between perceptual processors and relay nodes along their pathways, conferring selective advantages by linking current inputs with a history of weighted input values
neural subjective frame	original formulation	consciousness depends on neural maps of the bodily state, providing a first-person perspective	[172]
	substitutions	neural $\to$ system/processor; bodily $\to$ environmental interface
	expanded aneurocentric formulation	consciousness is a dynamic frame of reference that is dependent on continuously updated maps of the system’s internal states that do not directly interface with the environment, but which are impinged upon by processors of external stimulation
neuro-representationalism	original formulation	consciousness depends on multi-level neurally encoded predictive representations	[173]
	substitutions	neurally $\to$ non-environment/system

(Continued.)

Table 1. (Continued.)

theory	primary claim		references
	expanded aneurocentric formulation	consciousness is a multi-modal, context-dependent survey that predicts representations of input stimulation (i.e. superinferences) from the environment and enables goal-directed actions upon the environment
orchestrated objective reduction	original formulation	consciousness depends on quantum computations within microtubules inside neurons	link
	substitutions	microtubules $\to$ qubit reservoirs/processors neurons $\to$ cell/system
	expanded aneurocentric formulation	consciousness is the terminal product of complex, quantum computations performed by oscillating electromagnetic dipoles as qubits that undergo state reduction with a definite outcome
predictive processing	original formulation	perception depends on predictive inference of the causes of sensory signals; provides a framework for systematically mapping neural mechanisms to aspects of consciousness	link
	substitutions	sensory $\to$ inputs neural $\to$ internal/processor
	expanded aneurocentric formulation	consciousness arises from the process of actively testing hypotheses as internal predictive models of expected inputs against streams of actual inputs
sensorimotor theory	original formulation	consciousness depends on mastery of the laws governing sensorimotor contingencies	link
	substitutions	sensorimotor $\to$ input-output/embodiment
	expanded aneurocentric formulation	consciousness is a system’s capacity to display embodied engagement (output) with stimuli (input) from the environment without the necessity of internal representations
self comes to mind theory	original formulation	consciousness depends on interactions between homeostatic routines and multi-level interoceptive maps, with affect and feeling at the core	link
	substitutions	none
	expanded aneurocentric formulation	consciousness is a state that occurs when a system contains an informationally closed internal representation of itself, situated relative to an external environment.
self-organizing meta-representational theory	original formulation	consciousness is the brain’s (meta-representational) theory about itself	link
	substitutions	brain $\to$ system
	expanded aneurocentric formulation	consciousness occurs in systems that can attend to their first-order internal states, which are generated by impinging external stimuli, and have learnt to value some states over others

(Continued.)

Table 1. (Continued.)

theory	primary claim		references
unlimited associative learning	original formulation	consciousness depends on a form of learning that enables an organism to link motivational value with stimuli or actions that are novel, compound and non-reflex inducing	[183,184]
	substitutions	organism $\to$ system
	expanded aneurocentric formulation	consciousness arises when a system’s states are processed by high-level integrating units, learning about itself in an open-ended way with compounds of paired patterns of stimuli and actions

When the substrate- and scale-dependent contents of each theory are separated from their functional principles, it becomes clear that, among the most prominent ToCs, there are only a handful of distinct concepts or themes including: (i) predictive modelling, (ii) enactivism/ecological interactions, (iii) re-entrancy or looped feedback, (iv) meta-representations, (v) attentional gating/monitoring, (vi) emergence from computation, (vii) integration of information, and (viii) coarse-graining. Some ToCs are mutually incompatible; however, viewed through a functionalist lens, many more display broad conceptual overlap. While there is no doubt that particular brain regions (e.g. cortices, brainstem nuclei), networks (e.g. default mode network, attentional, sensorimotor) and circuits (e.g. corticothalamic), as well as neurophysiological processes (e.g. gamma oscillations) are at least necessary for human brains to generate consciousness, efforts to extend ToCs to other minds must involve a generalization and analysis of the biological details of such theories to test mappings of the theory onto functions of all cells (and thus organs). Aneurocentric formulations of ToCs are thus testable while enabling a comparative analysis of consciousness across very different systems.

4. Implications of consciousness in agents living in unconventional spaces

Observable phenomena by which we typically infer some degree of consciousness, including learning, decision-making, navigation, eye tracking and goal-directedness, typically occur in three-dimensional behavioural space at familiar, human-centred scales. However, it is now known that many cells, tissues and aneural organs can do all of these things in metabolic, physiological, transcriptional (gene expression) and anatomical spaces ([19]; figure 4). They formulate and pursue goals, solve new problems they have not seen before, exhibit taxis and aversive behaviour with respect to regions of their state space and align components towards large-scale goals (reviewed in [14,64,65,119,134,191–193]). Indeed, it appears that the interesting properties of brains arose as a gradual evolutionary pivot of fundamental capacities (including active inference and homeodynamic goal-directedness) across problem spaces [93]. While difficult for us to visualize directly, because of our sense organs and our own evolved theory-of-mind firmware focused on a fixed range of embodiments and behaviours involving obvious motility, it is essential to let advances in science expand our native perspective. To the extent that research in basal cognition and diverse intelligence reveals behavioural competencies in unconventional spaces, we must be open to the applicability of ToCs to these scenarios. As seen in table 1, and consistent with the very high conservation of mechanisms and algorithms between neurons and non-neural cells, no existing ToC rules out aneural substrate. For precisely the same reasons, we routinely entertain the possibility of consciousness in brainy animals based on their behaviour and its biophysical underpinning, we must consider the possibility that cells, tissues, organs, organoids, biobots and a wide range of chimeric cyborg/

hybrots architectures could have inner experience as they intelligently navigate, strive, achieve and suffer in their own worlds of possibility. And indeed, as known from advances in the field of morphological computation [194–196], the structure of an agent’s problem space has a massive impact on their embodiment and cognition, which suggests that minds navigating unconventional spaces may not be easy for us to detect unaided.

5. Developing research programmes

This perspective, grounded in developmental and evolutionary biology of the biophysics underlying neural networks, has a number of implications for a research roadmap. The use of tools and concepts of neuroscience and behavioural science is already paying off in terms of empirical discoveries and new experimental vistas in these fields, for example, in the use of the collective intelligence of cells navigating anatomical morphospace to impact birth defects, regeneration and cancer (reviewed in [91,197,198]) and the investigation of learning and memory in gene-regulatory networks with possible impacts on a wide range of pharmacological use cases [33,34,199,200]. But to date, these have all been strictly third-person perspective, standard science. It is time to extend consciousness studies and philosophy of mind to cell biology, regenerative medicine and bioengineering.

An obvious next step is to use metrics from causal information theory and IIT (integrated information theory [201,202])integrated information theory to study the information flows during behaviour in non-neural agents [203]. This has already begun, in work to measure information architecture [204] and causal emergence metrics in Xenobots [205] and gene-regulatory networks [206]. Many other substrates, such as calcium and bioelectric signalling, during embryonic and regenerative morphogenesis [207], carcinogenic transformation [208,209] and self-assembly of biobots [73,74,210,211], remain to be tested. We also envision the development of classic tools, such as the mirror test and variants of the Turing test, in spaces that make them applicable to cells and similar unconventional agents.

One of the key lynchpins in discussions of both AI and organoid consciousness has been the criterion of embodiment [89,212–216]. Many have argued that engagement with a rich action space via a perception-action loop (including perceptual control [217] or active inference [218–220]) is critical for the formation of true agents with consciousness. We agree, but point out that movement in three-dimensional space is not the only arena for this critical dynamic. It is possible that ‘disembodied’ organoids, for example, which offer no obvious behaviour in three-dimensional space (because they lack muscles and other effectors), in fact display a kind of ‘locked-in syndrome’ [221] that makes observers think there is no one inside, whereas they have an active life, solving problems in gene expression, physiological and other spaces. For the same reasons we seek to develop tools to identify inner perspective in human cases of locked-in syndrome or coma [54,55], we must broaden our perspective and create substrate-agnostic conceptual and experimental tools to detect, quantify and characterize these processes across the diverse agential material of life, from sub-cellular molecular networks to organ systems. We hypothesize that the existing tools of the neuroscience of consciousness, combined with virtual reality tools to assist visualization of behaviour in high-dimensional, unconventional spaces by human scientists, will be a powerful combination to begin to overcome our innate inability to see all but a tiny fraction of the endless, most beautiful [222] forms of minds.

By loosening historical constraints on the nature of conscious embodiments and the spaces within which they must navigate, the science of consciousness gains access to a wide range of beings that, while seemingly alien, are functionally familiar. Many questions abound with respect to the kinds of minds that exo-biological life forms would have; while we do not have access to true aliens, we now have the opportunity to try to understand minds that are on the same evolutionary tree as us, and thus perhaps tractable, but will force us to expand and refine our conceptual apparatus because they are not tractable to anthropocentric, brain-focused formalisms. The recognition of possible consciousness in living material more broadly

Figure 4. Morphogenesis as behaviour of cellular collective intelligence in morphospace. (A) Human embryos split in half give rise to monozygotic twins (and higher multiples), not half-bodies, illustrating that development is not a hardwired but a flexible, context-sensitive process that can accommodate novel perturbations to reach its goal. (B) More generally, represented in a two-dimensional schematic of morphospace (a high-dimensional space of possible anatomical configurations), normal embryos (S1) can reach the ensemble of goal states (G) representing a normal species-specific target morphology, but in many life forms, so can embryos split in half (S2) or undergo a wide range of other perturbations (S3, S4). This ability to reach their goal from different starting positions in the space, often avoiding getting stuck in local maxima (LM), represents a kind of navigational problem-solving. (C) Some animals maintain this in adulthood, such as limb regeneration in amphibians: the appendage can be cut at any level and then regenerates the precise amount and shape of missing materials, stopping when a correct limb is produced. This capacity, along with regulative embryogenesis, is a kind of error minimization loop that is carried out by cells, all of which are aligned towards a large-scale goal in the anatomical space. (D) Another example of flexible pursuit of goals by non-neural cells is the formation of a frog face from the reorganization of tadpole craniofacial organs, which can begin in their normal positions or a scrambled (Picasso-like) state, because the paths they take are not hardwired but adjusted dynamically to reach the correct pattern despite unexpected starting configurations [185]. (E) The goal state, with respect to which cellular effectors operate in these cases, can be stored as a bioelectrical pattern memory, akin to the storage of goal states in neural memory systems [11]; here is shown one example—the ‘electric face’ pattern ([186]; visualized with a bioelectrical reporter dye), which instructs the location of the components of the face. Voltage imaging in non-neural cells now allows the read-out (and increasingly, decoding) of the information patterns in bioelectric networks that guide behaviour towards specific future states. (F) Cross section of kidney tubules in normal versus polyploid newts. As polyploidy increases, it causes an increase in cell size, but the overall structure remains normal because the cells adjust by having fewer cells participate in the process. The right panel shows the most extreme case, where the cells are so big that they use a different molecular mechanism to accomplish the goal (by having one cell wrap around itself). Panel A used with permission from Oudeschool via Wikimedia Commons. Panel C used with permission from [187]. Panel D: top left image used with permission from [188]; bottom left image used with permission from [186]. Right image courtesy of Erin Switzer, Levin lab, and modified after [40]. Panel E used with permission from [186]. Panel F adapted from [189], used with permission from [190]. Panels C and F by Jeremy Guay of Peregrine Creative.

will recalibrate current debates about octopuses, crustaceans, plants, etc., and raise fascinating
questions about ethical relationships with this much broader class of beings.

6. Conclusion

Taking the slow, gradual scale-up seriously from single cells revealed by developmental and
evolutionary biology makes the continuity thesis the null hypothesis. The high conservation of

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mechanisms and behaviours in brains all the way back to pre-cellular material implies that a kind of panpsychism, committed to understanding the scaling and transformation of embodied minds from physical dynamics, is not only viable but should also be the baseline assumption. Indeed, our approach places consciousness on a functional continuum not unlike any other capacity. The claim that an organism (or any system) is or is not conscious is, in our view, equivalent to the claim that an organism can or cannot fly, swim, see, hear or carry out any particular function. Rather than forcing binary categorization, it may be useful instead to ask about the degree to which an organism is able to resist gravity, displace fluids or transduce waveforms. Competing ideas, relying on sharp phase transitions and brain-specific theories, need to specify principled reasons for discontinuities and explain the ‘emergence’ of novel natural kinds.

The state of the art in physiology and diverse intelligence research, combined with the compatibility of current ToCs with aneural substrates, suggests that consciousness may be common throughout the body. Our mind supervenes on a collection of cells, working together by means of a bioelectric network that aligns them towards larger cognitive light cones in abstract problem spaces. That architecture is ubiquitous throughout our bodies and throughout evolution. Thus, consciousness in a collective intelligence made of cells is not a wild claim—indeed, it is the only kind of consciousness we have ever seen, because each of us is a collective intelligence (of neurons). For all the reasons discussed above, we can drop the part in parentheses from the list of requirements and get on with the task of understanding collective intelligence in all of its general guises and the ways in which it enables intelligence to come into the world.

But it is often objected: ‘we don’t feel our liver being conscious!”. While that is true, we do not feel each other being conscious either. Indeed, if the liver or its parts were capable of subjective experience, that point of view would be quite independent from the consciousness of a brain with which it shared a body. We suggest dropping the unfounded requirement that a body has only one consciousness, as well as the privileged perspective of the one body organ that can eloquently proclaim its lonely unity by way of the left hemisphere’s capacity for language. Many brain structures are mirrored across hemispheres and can function independently following interhemispheric disconnections, including callosotomy. While perception can clearly be divided into split-brain patients, the evidence for divided consciousness is mixed [223], in part because of a shared body (which makes discernment of dual nature by outside observers, or even by one of the hemispheres, challenging). However, if each hemisphere were reciprocally connected to its own independent body, evidence from hybrid robotics research would predict unique behavioural correlates of consciousness suggestive of a capacity for multiple subjects within a shared body. At this point, there is no evidence that the consciousness of non-brain body organs would be the complex, self-reflexive consciousness enjoyed by the human mind or would be capable of language. But this still leaves a huge swath of the consciousness spectrum, which biology likely occupied in its journey from physics. By expanding into the field of diverse intelligence and unconventional embodiments, we can begin to truly deal with the problem of other minds and the richness of conscious kin both within and around us.

**Data accessibility.** This article has no additional data. **Declaration of AI use.** We have not used AI-assisted technologies in creating this article. **Authors’ contributions.** N.R.: conceptualization, writing—original draft, writing—review and editing; M.L.: conceptualization, writing—original draft, writing—review and editing. Both authors gave final approval for publication and agreed to be held accountable for the work performed therein. **Conflict of interest declaration.** M.L. is an advisor to a company called Softmax, which seeks to operate in the space of artificial intelligence. **Funding.** We gratefully acknowledge the support of Eugene Jhong and of the Army Research Office under grant number W911NF-23-1-0100. The views and conclusions contained in this document are those of the authors and should not be interpreted as representing the official policies, either expressed or implied,

of the Army Research Office or the US Government. We also acknowledge support from the Natural Sciences and Engineering Research Council of Canada (NSERC: RGPIN-2022-04162) and the New Frontiers in Research Fund Exploration Grant (NFRF-EG: NFRFE-2023-00568).

Acknowledgements. We thank Daniel C. Dennett, Chris Fields, Karl Friston, Pamela Lyon, Anil Seth, Mark Solms and many other members of the community for numerous helpful discussions. We thank Julia Poirier for invaluable assistance with manuscript preparation.

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