This article is a commentary on Jonathan Birch's The edge of sentience . It considers the role of deference to consciousness experts in the citizens' assemblies that he calls for; evaluates his claim that the human fetus is a sentience candidate from 12 weeks' gestation; and explores some of the issues raised by his approach to sentience in large language models and other AI systems.

Hemispherotomy is a neurosurgical procedure for treating refractory epilepsy, which entails disconnecting a significant portion of the cortex, potentially encompassing an entire hemisphere, from its cortical and subcortical connections. While this intervention prevents the spread of seizures, it raises important questions. Given the complete isolation from sensory-motor pathways, it remains unclear whether the disconnected cortex retains any form of inaccessible awareness. More broadly, the activity patterns that large portions of the deafferented cortex can sustain in awake humans remain poorly understood. We address these questions by exploring for the first time the electrophysiological state of the isolated cortex before and after surgery in ten awake pediatric patients. Post-surgery, the isolated cortex exhibited prominent slow oscillations (<2 Hz) and a broad-band shift in power spectral density from high to low frequencies. This resulted in a marked decrease of the spectral exponent, a validated consciousness marker, indicating broad-band slowing characteristic of unconscious states. When compared with a reference pediatric sample across the sleep-wake cycle, the spectral exponent of the contralateral cortex aligned with wakefulness, whereas that of the isolated cortex was consistent with deep NREM sleep. However, spindles did not emerge in the isolated cortex due to the lack of subcortical inputs, constituting a fundamental difference from physiological sleep. These findings demonstrate a unihemispheric sleep-like state during wakefulness, challenging the possibility that hemispherotomy might lead to inaccessible "islands of awareness." Moreover, the persistence of sleep-like patterns years after disconnection provides unique insights into the electrophysiological effects of disconnections in the human brain. ### Competing Interest Statement I have read the journal's policy and the authors of this manuscript have the following competing interests: M.M. is co-founder and shareholder of Intrinsic Powers, Inc., a spin-off of the University of Milan Si.Sa. is advisor of the same company. The remaining co-authors have no conflicts of interest to declare.

A foundational issue for the science and philosophy of consciousness concerns the function(s) of consciousness-what consciousness does for any particular aspect of psychological or neural processing. In spite of progress in consciousness science, false assumptions and a lack of clarity regarding how best to approach the functions of consciousness represent an ongoing and serious roadblock to progress. Misguided approaches to the function(s) of consciousness have the potential to mangle explanatory priorities, and divert attention, effort, and funding away from useful questions and experimental paradigms. In this paper we offer a way forward: the capacity-based approach to the function(s) of consciousness. This approach flows out of a general explanatory approach that is influential in the philosophy of science and psychology (but not consciousness studies), according to which the mind is understood in terms of a structured collection of capacities. And capacities are explained by empirically discovered facts that identify functions (causal roles) played by empirically identified parts of a system. After elucidating this capacity-based approach to the mind, we show how consciousness fits within it. We then argue that this approach avoids problems that plague theory-based approaches to identifying the function(s) of consciousness, avoids mistakes endemic to the common strategy of looking for the function(s) of consciousness by asking what consciousness is necessary for, and re-orients explanatory priorities in a way that better focuses consciousness science, and that suggests fruitful avenues for experimentation.

Hemispherotomy is a neurosurgical procedure for treating refractory epilepsy, which entails disconnecting a significant portion of the cortex, potentially encompassing an entire hemisphere, from its cortical and subcortical connections. While this intervention prevents the spread of seizures, it raises important questions. Given the complete isolation from sensory-motor pathways, it remains unclear whether the disconnected cortex retains any form of inaccessible awareness. More broadly, the activity patterns that large portions of the deafferented cortex can sustain in awake humans remain poorly understood. We address these questions by exploring for the first time the electroencephalographic (EEG) state of the isolated cortex during wakefulness before and after surgery in 10 pediatric patients, focusing on non-epileptic background activity. Post-surgery, the isolated cortex exhibited prominent slow oscillations (<2 Hz) and a steeper broad-band spectral decay, reflecting a redistribution of power toward lower frequencies. This broad-band EEG slowing resulted in a marked decrease of the spectral exponent, a validated consciousness marker, reaching values characteristic of deep anesthesia and the vegetative state. When compared with a reference pediatric sample across the sleep-wake cycle, the spectral exponent of the contralateral cortex aligned with wakefulness, whereas that of the isolated cortex was consistent with deep NREM sleep. The findings of prominent slow oscillations and broad-band slowing provisionally support inferences of absent or reduced awareness in the isolated cortex. Moreover, the persistence of unihemispheric sleep-like patterns years after surgery provides unique insights into the long-term electrophysiological effects of cortical disconnections in the human brain.

Rapid progress in artificial intelligence (AI) capabilities has drawn fresh attention to the prospect of consciousness in AI. There is an urgent need for rigorous methods to assess AI systems for consciousness, but significant uncertainty about relevant issues in consciousness science. We present a method for assessing AI systems for consciousness that involves exploring what follows from existing or future neuroscientific theories of consciousness. Indicators derived from such theories can be used to inform credences about whether particular AI systems are conscious. This method allows us to make meaningful progress because some influential theories of consciousness, notably including computational functionalist theories, have implications for AI that can be investigated empirically.

As recently as the 1980s, it was not uncommon for paediatric surgeons to operate on infants without anaesthesia. Today, the same omission would be considered criminal malpractice, and there is an increased concern with the possibility of consciousness in the earliest stage of human infancy. This concern reflects a more general trend that has characterised science since the early 1990s of taking consciousness seriously. While this attitude shift has opened minds towards the possibility that our earliest experiences predate our first memories, convincing demonstrations of infant consciousness remain challenging given that infants cannot report on their experiences. Furthermore, while many behavioural and neural markers of consciousness that do not rely on language have been validated in adults, no one specific marker can be confidently translated to infancy. For this reason, we have proposed the 'cluster-based' approach, in which a consensus of evidence across many markers, all pointing towards the same developmental period, could be used to argue convincingly for the presence of consciousness. CONCLUSION: We review the most promising markers for early consciousness, arguing that consciousness is likely to be in place by 5 months of age if not earlier.

Which systems/organisms are conscious? New tests for consciousness (‘C-tests’) are urgently needed. There is persisting uncertainty about when consciousness arises in human development, when it is lost due to neurological disorders and brain injury, and how it is distributed in nonhuman species. This need is amplified by recent and rapid developments in artificial intelligence (AI), neural organoids, and xenobot technology. Although a number of C-tests have been proposed in recent years, most are of limited use, and currently we have no C-tests for many of the populations for which they are most critical. Here, we identify challenges facing any attempt to develop C-tests, propose a multidimensional classification of such tests, and identify strategies that might be used to validate them.

This paper addresses the question of whether large language model-powered chatbots are capable of assertion. According to what we call the Thesis of Chatbot Assertion (TCA), chatbots are the kinds of things that can assert, and at least some of the output produced by current-generation chatbots qualifies as assertion. We provide some motivation for TCA, arguing that it ought to be taken seriously and not simply dismissed. We also review recent objections to TCA, arguing that these objections are weighty. We thus confront the following dilemma: how can we do justice to both the considerations for and against TCA? We consider two influential responses to this dilemma - the first appeals to the notion of proxy-assertion; the second appeals to fictionalism - and argue that neither is satisfactory. Instead, reflecting on the ontogenesis of assertion, we argue that we need to make space for a category of proto-assertion. We then apply the category of proto-assertion to chatbots, arguing that treating chatbots as proto-assertors provides a satisfactory resolution to the dilemma of chatbot assertion.

When does the mind begin? Infant psychology is mysterious in part because we cannot remember our first months of life, nor can we directly communicate with infants. Even more speculative is the possibility of mental life prior to birth. The question of when consciousness, or subjective experience, begins in human development thus remains incompletely answered, though boundaries can be set using current knowledge from developmental neurobiology and recent investigations of the perinatal brain. Here, we offer our perspective on how the development of a sensory perturbational complexity index (sPCI) based on auditory (“beep-and-zip”), visual (“flash-and-zip”), or even olfactory (“sniff-and-zip”) cortical perturbations in place of electromagnetic perturbations (“zap-and-zip”) might be used to address this question. First, we discuss recent studies of perinatal cognition and consciousness using techniques such as functional magnetic resonance imaging (fMRI), electroencephalography (EEG), and, in particular, magnetoencephalography (MEG). While newborn infants are the archetypal subjects for studying early human development, researchers may also benefit from fetal studies, as the womb is, in many respects, a more controlled environment than the cradle. The earliest possible timepoint when subjective experience might begin is likely the establishment of thalamocortical connectivity at 26 weeks gestation, as the thalamocortical system is necessary for consciousness according to most theoretical frameworks. To infer at what age and in which behavioral states consciousness might emerge following the initiation of thalamocortical pathways, we advocate for the development of the sPCI and similar techniques, based on EEG, MEG, and fMRI, to estimate the perinatal brain's state of consciousness.

The cognitive phenomenology debate concerns the nature of conscious thought. On one side of the debate are those who deny that thought has a sui generis phenomenal character. This view—which I refer to as ‘conservatism’—holds that to the extent that thoughts are phenomenally conscious, their phenomenal character is purely sensory. On the other side of the debate are those who hold that thought is characterized by sui generis non-sensory phenomenal states—‘cognitive phenomenology’. My concern in this chapter is not with the question of whether cognitive phenomenology exists, but with the very debate about itself: why do philosophers of mind disagree about the nature of conscious thought? I argue for a semantic analysis of this debate: conservatives and liberals lack a shared conception of what cognitive phenomenology would be. I go on to argue that the real lesson of the cognitive phenomenology debate is that there may be no unitary concept of phenomenal consciousness.

Consciousness is—or is alleged to be—related to free will in a number of ways. This chapter distinguishes two main points of contact. The first is related to belief in the existence of free will. Here, it is argued that one might appeal to the experience of freely willing an action to explain why belief in the reality of free will is widespread and/or to explain why that belief is true (or at least reasonable). The second point of contact between consciousness and free action/will holds that consciousness is in some way necessary for free action/will. The chapter considers this proposal in light of a number of distinctions: between consciousness as a property of agents and consciousness as a property of mental state, and between consciousness understood as wakefulness and consciousness understood as experience.

Recent years have seen a blossoming of theories about the biological and physical basis of consciousness. Good theories guide empirical research, allowing us to interpret data, develop new experimental techniques and expand our capacity to manipulate the phenomenon of interest. Indeed, it is only when couched in terms of a theory that empirical discoveries can ultimately deliver a satisfying understanding of a phenomenon. However, in the case of consciousness, it is unclear how current theories relate to each other, or whether they can be empirically distinguished. To clarify this complicated landscape, we review four prominent theoretical approaches to consciousness: higher-order theories, global workspace theories, re-entry and predictive processing theories and integrated information theory. We describe the key characteristics of each approach by identifying which aspects of consciousness they propose to explain, what their neurobiological commitments are and what empirical data are adduced in their support. We consider how some prominent empirical debates might distinguish among these theories, and we outline three ways in which theories need to be developed to deliver a mature regimen of theory-testing in the neuroscience of consciousness. There are good reasons to think that the iterative development, testing and comparison of theories of consciousness will lead to a deeper understanding of this most profound of mysteries.

This chapter considers three approaches to the question “What kind of behavioral experiments, if any, could determine whether anyone has free will?” The first approach might be adopted by those who hold that some agents (e.g., young children and non-human animals) lack free will, whereas others (e.g., neurotypical humans) possess it. Given this perspective, behavioral experiments that distinguish infants and non-human animals from neurotypical human agents could be relevant to adjudicating whether a target individual has free will. A second approach is skeptical that anyone has free will. The worries that animate most free-will skeptics cannot be resolved by appeal to behavioral experiments. A third approach concerns the concept of free will. Here, there is a rich literature in experimental philosophy that employs behavioral methods to clarify the ordinary concept of free will.