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| Haikouichthys. (A) Artist's rendering of what Haikouichthys looked like. (B) Fossil of this animal with an eye and otic capsule ("Auditory vesicle") labeled. Haikouichthys is agreed to have been a true vertebrate, a jawless fish, and it shows vertebral elements (protovertebrae), prominent eyes, and nasal capsules (Shu, 2003; Shu et al., 2003, 2009). From Figure 146 in Chen (2012) Springer. Reprinted with kind permission from Springer Science+Business Media B.V.
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Vertebrates evolved in the Cambrian Period before 520 million years ago, but we do not know when or how consciousness arose in the history of the vertebrate brain. Here we propose multiple levels of isomorphic or somatotopic neural representations as an objective marker for sensory consciousness. All extant vertebrates have these, so we deduce that...
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... should be noted, however, that the interpretation of the Haikouella fossils is not without controversy. Most prominently, Shu and co-workers have questioned Haikouella's evolutionary placement and even the existence of eyes, a notochord, or a brain in this animal ( Shu et al., 1996Shu et al., , 2009Shu, 2003;also see Donoghue and Purnell, 2009). This leaves another 520-million- year-old group from the same fossil beds, Haikouichthys ercai- cunensis ( Figure 6) and related species, as best indicating the early evolution of the vertebrate nervous system ( Shu et al., 1999Shu et al., , 2003Shu et al., , 2009Hou et al., 2002;Shu, 2003;Chen, ...
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... The gnathostome and agnathan lineages are supposedly diverged in the Paleozoic, early in the evolutionary history of vertebrates. It is assumed that this divergence could have occurred as early as the Cambrian, at a time horizon of approximately 535-462 million years ago (Janvier, 2006;Kuraki and Kuratani, 2006;Feinberg and Mallatt, 2013). Priscomyzon riniensis is currently described as the oldest fossil lamprey (Gess et al., 2006). ...
... However, as more is learned about animal behaviour, that view is quickly fading. During the Cambrian explosion, early vertebrates emerged with the cognitive capacity for subjective experience (Feinberg and Mallatt 2013;Jablonka 2010, 2019;Godfrey-Smith 2017) and episodic-like memory (Schultz 2024;Zacks, Ginsburg, and Jablonka 2022) that have enabled learning, planning and cooperation (Busia and Griggio 2020;Croft et al. 2006;Heathcote et al. 2017). Over the last several decades, research has revealed that fishes' cognitive capacity and behavioural flexibility are not overly different from most vertebrates (Brown, Laland, and Krause 2011;Bshary and Brown 2014;Budaev et al. 2024;Giske et al. 2025;Salena et al. 2021). ...
Social learning is common among vertebrates, including fish. Learning from others reduces the risk and costs of adaptation. In some longer‐lived species, social learning can lead to the formation of persistent groups that pass learned adaptations from one generation to the next (culture). Variations in learned adaptations are subject to natural selection, leading to a second, fast‐paced, fine‐scale evolutionary process that complements genetics and enables adaptation to the peculiarities of local areas. Socially learned knowledge is stored mainly in the minds of older fish and subsequently inherited (learned) by younger fish. Consequently, the persistence of locally adapted groups of long‐lived fish requires the inheritance of genetic and learned adaptations. Local populations of social learners are not often recognised nor conserved by fisheries managers. Fishing usually reduces the relative abundance of older fish far more than younger. We hypothesise that fishing may impair and eventually erase the learned local adaptations of long‐lived fish, leading to the loss of local stocks of these species and significant ecosystem‐wide changes. Fishing may shift abundance towards species not dependent on learned adaptations, i.e., invertebrates and short‐lived fish. The hypothesis leads directly to the idea that conserving populations of long‐lived social learners is likely best accomplished by protecting age and social structure or, more generally, the natural processes, such as social learning, that generate complexity in an adaptive ecosystem. Local area‐based management is aligned with the local processes of social learners and can capture and learn about the effect of human activity at that scale.
... The three main stages of neurulation are illustrated sequentially (adapted from[33]). (A) Neural plate: A flat layer of ectoderm begins to bend as cells change their shape, laying the foundation for subsequent structures. (B) Neural folds: The folds elevate and converge toward the midline, facilitating the closure of the neural tube. ...
... (B) Neural folds: The folds elevate and converge toward the midline, facilitating the closure of the neural tube. (C) Neural tube: Once closed, this structure develops further into the central nervous system[33]. ...
Neural tube defects (NTDs) are malformations of the central nervous system that represent the second most common cause of congenital morbidity and mortality, following cardiovascular abnormalities. Maternal nutrition, particularly folic acid, a B vitamin, is crucial in the etiology of NTDs. FA plays a key role in DNA methylation, synthesis, and repair, acting as a cofactor in one-carbon transfer reactions essential for neural tube development. Randomized trials have shown that FA supplementation during preconceptional and periconceptional periods reduces the incidence of NTDs by nearly 80%. Consequently, it is recommended that all women of reproductive age take 400 µg of FA daily. Many countries have introduced FA fortification of staple foods to prevent NTDs, addressing the high rate of unplanned pregnancies. These policies have increased FA intake and decreased NTD incidence. Although the precise mechanisms by which FA protects against NTDs remain unclear, compelling evidence supports its efficacy in preventing most NTDs, leading to national recommendations for FA supplementation in women. This review focuses on preconceptional and periconceptional FA supplementation in the female population of the Visegrad Group countries (Slovakia, Czech Republic, Poland, and Hungary). Our findings emphasize the need for a comprehensive approach to NTDs, including FA supplementation programs, tailored counseling, and effective national-level policies.
... In the science of consciousness, it is widely accepted that human and non-human animal consciousness evolved from earlier forms of experience possessed by our evolutionary ancestors, which themselves evolved from even more primitive forms, tracing back the origins of sentience to some point(s) in the evolutionary tree of life (Feinberg & Mallatt, 2013;Ginsburg & Jablonka, 2019;Godfrey-Smith, 2016;Veit, 2023). In other words, non-conscious forms of life eventually evolved and developed primordial forms of consciousness, probably due to the emergence of the right sort of nervous systems both in vertebrate and invertebrate animals (Birch, 2024;Damasio & Damasio, 2024;Denton, 2005;Godfrey-Smith, 2024;Humphrey, 2022). ...
This paper addresses a problem that arises from the ontological commitments of Integrated Information Theory (IIT) 4.0, particularly its stance that only conscious entities truly exist. This position leads to the "origin of consciousness problem": if non-conscious entities do not truly exist, how could consciousness have evolved from non-conscious ancestors? We explore several responses IIT might offer, such as the co-origin of life and consciousness, or the idea that non-conscious ancestors might have been constituted by "ontological dust"—minimally conscious, intrinsic micro-entities collectively aggregated to form bigger objects lacking unified consciousness. Our analysis shows that IIT’s ontological framework, along with scientific knowledge regarding biological evolution, prebiotic chemical structures, and physical cosmology, ultimately forces the theory into positing a form of "Big Bang consciousness", that is, a primordial ontological dust constituted by minimally conscious elementary particles created soon after the Big Bang. Although IIT may accept this striking implication, we think that it introduces tensions with both the received scientific view of the evolutionary origin of consciousness and the cosmological understanding of early universe components. We also present but ultimately reject an alternative option based on what we call the “formless stuff hypothesis”, which might avoid the implication that consciousness originates from nothing as well as the necessity of a "Big Bang consciousness”. We conclude by suggesting that IIT's metaphysical commitments, especially the equation true existence=phenomenal existence, require re-examination to reconcile its framework with standard scientific knowledge, and in particular, with the received view about the phylogenetic origin of consciousness.
... Neural field theories of consciousness, whether they relate to representational fields, where Gestalten or qualia are seen as reflecting the very nature of consciousness, occupying a presumed spatiotemporal brain field generating electrical brain states [34], or to the functionally specific spatio-temporal structure of an electromagnetic field in the brain [38,39,40] only account for specific aspects of brain-behavior function while humans are in a conscious or non-conscious state. Yet, as already clarified here above, consciousness is a complex product of a long process of brain evolution, at the phylogenic [44] and ontogenic [45,46] scales. The problem of a scientific account for the origin of mind or, more specifically, the origin of consciousness, has arisen some time ago. ...
... Consciousness is a complex product of a long process of brain evolution [44,45]. ...
This chapter critically questions the claim that there would be possibility of emulating human consciousness and consciousness-dependent activity by Artificial Intelligence to create conscious artificial systems. The analysis is based on neurophysiological research and theory. In-depth scrutiny of the field and the prospects for converting neuroscience research into the type of algorithmic programs utilized in computer-based AI systems to create artificially conscious machines leads to conclude that such a conversion is unlikely to ever be possible because of the complexity of unconscious and conscious brain processing and their interaction. It is through the latter that the brain opens the doors to consciousness, a property of the human mind that no other living species has developed for reasons that are made clear in this chapter. As a consequence, many of the projected goals of AI will remain forever unrealizable. Although this work does not directly examine the question within a philosophy of mind framework by, for example, discussing why identifying consciousness with the activity of electronic circuits is first and foremost a category mistake in terms of scientific reasoning, the approach offered in the chapter is complementary to this standpoint, and illustrates various aspects of the problem under a monist from-brain-to-mind premise.
Keywords: Consciousness, Brain, Artificial Consciousness, Human Mind
... 10,13 Aunque esta hipótesis tiene menos consenso entre la comunidad científica, también establece una posible función sensitiva de estas estructuras antiguas. 10,14 La percepción primitiva de sensaciones mecánicas, osmóticas, químicas y de temperatura apareció en las especies hace unos 500 millones de años, 15 las escamas, placas y tubérculos dérmicos que dieron origen a los dientes, eran en sí, sistemas de percepción del entorno, es decir, nuestros órganos dentarios tuvieron un origen sensor millones de años antes de que dieran paso a su función masticatoria. ...
... example of this type of model is the research of Nikos Logothetis and colleagues(LOGOTHETIS & SCHALL, 1989; SCHEINBERG & LOGOTHETIS, 1997), in which the authors employ methodologies of the type of multistable visual stimuli as the paradigms of Binocular Rivalry (BR).Differently, category (2) corresponds to phylogenetic studies of consciousness in non-human animals that investigate the distribution of consciousness among phyla and its origin(CARRUTHERS 2000;FEINBERG & MALLATT, 2013). Therefore, the question of which lineages (whether species, classes, or phyla) of animals are conscious is inevitably still intertwined with considerations about the evolutionary origin of consciousness (LEDOUX, 2019). ...
... Consciousness is a complex product of a long process of brain evolution (e.g. Cabanac, Cabanac, and Parent, 2009;Feinberg and Mallatt, 2013). Since the theory of evolution was carved out by Darwin (1871), the problem of a scientific account for the origin of mind or more specifically the origin of consciousness, had arisen. ...
The rise of Artificial Intelligence (AI) has produced prophets and prophecies announcing that the age of artificial consciousness is near. Not only does the mere idea that any machine could ever possess the full potential of human consciousness suggest that AI could replace the role of God in the future, it also puts into question the fundamental human right to freedom and dignity. Yet, in the light of all we currently know about brain evolution and the adaptive neural dynamics underlying human consciousness, the idea of an artificial consciousness appears misconceived. This article highlights some of the major reasons why the prophecy of a successful emulation of human consciousness by AI ignores most of the data about adaptive processes of learning and memory as the developmental origins of consciousness. The analysis provided leads to conclude that human consciousness is epigenetically determined as a unique property of the mind, shaped by experience, capable of representing real and non-real world states and creatively projecting these representations into the future. The development of the adaptive brain circuitry that enables this expression of consciousness is highly context-dependent, shaped by multiple self-organizing functional interactions at different levels of integration displaying a from-local-to global functional organization. Human consciousness is subject to changes in time that are essentially unpredictable. If cracking the computational code to human consciousness were possible, the resulting algorithms would have to be able to generate temporal activity patterns simulating long-distance signal reverberation in the brain, and the de-correlation of spatial signal contents from their temporal signatures in the brain. In the light of scientific evidence for complex interactions between implicit (non-conscious) and explicit (conscious) representations in learning, memory, and the construction of conscious representations such a code would have to be capable of making all implicit processing explicit. Algorithms would have to be capable of a progressive and less and less arbitrary selection of temporal activity patterns in a continuously developing neural network structure that is functionally identical to that of the human brain, from synapses to higher cognitive functional integration. The code would have to possess the self-organizing capacities of the brain that generate the temporal signatures of a conscious experience. The consolidation or extinction of these temporal brain signatures are driven by external event probabilities according to the principles of Hebbian learning. Human consciousness is constantly fed by such learning, capable of generating stable representations despite an incommensurable amount of variability in input data, across time and across individuals, for a life-long integration of experience data. Artificial consciousness would require probabilistic adaptive computations capable of emulating all the dynamics of individual human learning, memory and experience. No AI is likely to ever have such potential.
... Consciousness is a complex product of a long process of brain evolution (e.g. Cabanac, Cabanac, and Parent, 2009;Feinberg and Mallatt, 2013). Since the theory of evolution was carved out by Darwin (1871), the problem of a scientific account for the origin of mind or more specifically the origin of consciousness, had arisen. ...
The rise of Artificial Intelligence (AI) has produced prophets and prophecies announcing that the age of artificial consciousness is near. Not only does the mere idea that any machine could ever possess the full potential of human consciousness suggest that AI could replace the role of God in the future, it also puts into question the fundamental human right to freedom and dignity. This position paper takes the stand that, in the light of all we currently know about brain evolution and the never-stopping formation of adaptive neural circuitry for learning, memory, decision making and, ultimately, fully conscious reasoning and creativity in the human species, the idea of an artificial consciousness appears misconceived. The paper highlights some of the major reasons why. While awareness to external stimuli for processes such as perception, recognition, and operational problem solving is under the direct control of functionally specific brain networks associated with sensory and cognitive functions across animal species, consciousness is a unique property of the human mind. Potentiated by brain evolution, consciousness has come to be when humans became able to represent, and reflect on, the Self in relation to past, present and future, and to project these representations into possible worlds by drawing and other forms of conceptual and creative expression. Epigenetically determined, shaped by experience, capable of representing real and non-real world states, consciousness is enabled by context-dependent adaptive brain circuits that have evolved on the grounds of self-organizing functional interactions at different levels of integration in a from-local-to global functional brain design. The evolution of the latter being continuous, the limits of consciousness are unpredictable. If cracking the computational code to human consciousness were possible, the resulting algorithms would have to be able to generate temporal activity patterns simulating long-distance signal reverberation across the brain and the de-correlation of spatial signal contents from their temporal signatures. In the light of scientific evidence for complex interactions between implicit (non-conscious) and explicit (conscious) representations in learning, memory, and the construction of conscious representation, the code would have to be capable of making all implicit processing explicit. Algorithms would have to be capable of a progressive, less and less arbitrary selection of temporal activity patterns in a continuously developing neural network structure akin to that of the human brain, from synapses to higher cognitive functional integration. The code would have to possess the self-organizing capacities that generate the brain signatures of phenomenal consciousness. In the biological brain, consolidation or extinction of these temporal brain signatures is driven by external event probabilities according to the principles of Hebbian learning. Consciousness is constantly fed by such learning, capable of generating stable representations despite an incommensurable amount of variability in input data, across time and across individuals, for life-long integration of experience data. Artificial consciousness would require probabilistic adaptive computations capable of emulating all the dynamics of human learning and memory that enable human intelligence and creativity. No AI is likely to ever have such potential.
... Throughout the rapid diversification of lifeforms during the 'Cambrian explosion'about 540 million years ago-the earliest chordates appeared [117]. Remarkably, but not surprisingly, genes regulating early chordate development are conserved among all vertebrate species, and the expression patterns of these early genes are remarkably similar across the entire vertebrate subphylum [118]. ...
A multitude of additional anomalies can be observed in virtually all types of symmetrical conjoined twins. These concomitant defects can be divided into different dysmorphological patterns. Some of these patterns reveal their etiological origin through their topographical location. The so-called shared anomalies are traceable to embryological adjustments and directly linked to the conjoined-twinning mechanism itself, inherently located within the boundaries of the coalescence area. In contrast, discordant patterns are anomalies present in only one of the twin members, intrin-sically distant from the area of union. These dysmorphological entities are much more difficult to place in a developmental perspective, as it is presumed that conjoined twins share identical intra-uterine environments and intra-embryonic molecular and genetic footprints. However, their existence testifies that certain developmental fields and their respective developmental pathways take different routes in members of conjoined twins. This observation remains a poorly understood phenomenon. This article describes 69 cases of external discordant patterns within different types of otherwise symmetrical mono-umbilical conjoined twins and places them in a developmental perspective and a molecular framework. Gaining insights into the phenotypes and underlying (bio-chemical) mechanisms could potentially pave the way and generate novel etiological visions in the formation of conjoined twins itself.
