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Publications (331)
Biological neural networks can perform complex computations to predict their environment, far above the limited predictive capabilities of individual neurons. While conventional approaches to understanding these computations often focus on isolating the contributions of single neurons, here we argue that a deeper understanding requires considering...
In daily life, we can not only estimate confidence in our inferences (‘I’m sure I failed that exam’), but can also estimate whether those feelings of confidence are good predictors of decision accuracy (‘I feel sure I failed, but my feeling is probably wrong; I probably passed’). In the lab, by using simple perceptual tasks and collecting trial-by-...
Hemispherotomy is a surgical procedure that disconnects a large portion of the cerebral cortex from cortical and subcortical inputs in patients with severe refractory epilepsy. Whether the disconnected cortex - inaccessible to behavioral assessment - supports consciousness remains unknown. Functional MRI studies have indicated preserved resting-sta...
Recent findings have shown that psychedelics reliably enhance brain entropy (understood as neural signal diversity), and this effect has been associated with both acute and long-term psychological outcomes, such as personality changes. These findings are particularly intriguing, given that a decrease of brain entropy is a robust indicator of loss o...
Visual hallucinations (VHs) are perceptions of objects or events in the absence of the sensory stimulation that would normally support such perceptions. Although all VHs share this core characteristic, there are substantial phenomenological differences between VHs that have different aetiologies, such as those arising from Neurodegenerative conditi...
Quantifying the complexity of neural activity has provided fundamental insights into cognition, consciousness, and clinical conditions. However, the most widely used approach to estimate the complexity of neural dynamics, Lempel-Ziv complexity (LZ), has fundamental limitations that substantially restrict its domain of applicability. In this article...
Quantifying the complexity of neural activity has provided fundamental insights into cognition, consciousness, and clinical conditions. However, the most widely used approach to estimate the complexity of neural dynamics, Lempel-Ziv complexity (LZ), has fundamental limitations that substantially restrict its domain of applicability. In this article...
Predictive coding is an influential model of cortical neural activity. It proposes that perceptual beliefs are furnished by sequentially minimising “prediction errors”—the differences between predicted and observed data. Implicit in this proposal is the idea that successful perception requires multiple cycles of neural activity. This is at odds wit...
Phenomenological control is the stable trait ability to alter subjective experience in accordance with goals. Although voluntary, phenomenological control is experienced as involuntary and has predominantly been studied within the context of hypnosis, in which direct verbal imaginative suggestions for a range of experiences are given by a designate...
Synaesthesia is a condition defined by additional perceptual experiences, which are automatically and consistently triggered by specific inducing stimuli. The associative nature of synaesthesia has motivated attempts to induce synaesthesia by means of associative learning. Two recent studies of this kind highlighted the potential for perceptual pla...
In daily life, we can not only estimate confidence in our inferences (“I’m sure I failed that exam”), but also estimate whether those feelings of confidence are good predictors of decision accuracy (“I feel sure I failed, but my feeling is probably wrong; I probably passed”). In the lab, visual metacognition research has repeatedly shown, using sim...
Perception can be shaped by our expectations, which can lead to perceptual illusions. Similarly, long-term memories can be shaped to fit our expectations, which can generate false memories. However, it is generally assumed that short-term memory for percepts formed just 1 or 2 seconds ago accurately represents the percepts as they were at the time...
Quantifying the complexity of neural activity has provided fundamental insights into cognition, consciousness, and clinical conditions. However, the most widely used approach to estimate the complexity of neural dynamics, Lempel-Ziv complexity (LZ), has fundamental limitations that substantially restrict its domain of applicability. In this article...
Extended reality (XR), encompassing various forms of virtual reality (VR) and augmented reality (AR), has become a powerful experimental tool in consciousness research due to its capability to create holistic and immersive experiences of oneself and surrounding environments through simulation. One hallmark of a successful XR experience is when it e...
The extent to which high-level, complex functions can proceed unconsciously has been a topic of considerable debate. While unconscious processing has been demonstrated for a range of low-level processes, from feature integration to simple forms of conditioning and learning, theoretical contributions suggest that increasing complexity requires consc...
Bruineberg and colleagues helpfully distinguish between instrumental and ontological interpretations of Markov blankets, exposing the dangers of using the former to make claims about the latter. However, proposing a sharp distinction neglects the value of recognising a continuum spanning from instrumental to ontological. This value extends to the r...
The experience of time passing is fundamental to human experience. Considerable experimental data has found that perceptual judgments of duration show systematic distortions away from physical ‘clock’ time. The majority of neurocognitive explanations of duration perception invoke some form of ‘inner clock’, or pacemaker. Systematic distortions can...
Schizophrenia and states induced by certain psychotomimetic drugs may share some physiological and phenomenological properties, but they differ in fundamental ways: one is a crippling chronic mental disease, while the others are temporary, pharmacologically-induced states presently being explored as treatments for mental illnesses. Building towards...
Human experience of time exhibits systematic, context-dependent deviations from clock time; for example, time is experienced differently at work than on holiday. Here we test the proposal that differences from clock time in subjective experience of time arise because time estimates are constructed by accumulating the same quantity that guides perce...
The integrated information theory of consciousness (IIT) is divisive: while some believe it provides an unprecedentedly powerful approach to address the ‘hard problem’, others dismiss it on grounds that it is untestable. We argue that the appeal and applicability of IIT can be greatly widened if we distinguish two flavours of the theory: strong IIT...
Human perception and experience of time are strongly influenced by ongoing stimulation, memory of past experiences, and required task context. When paying attention to time, time experience seems to expand; when distracted, it seems to contract. When considering time based on memory, the experience may be different than what is in the moment, exemp...
Emergence is a profound subject that straddles many scientific disciplines, including the formation of galaxies and how consciousness arises from the collective activity of neurons. Despite the broad interest that exists on this concept, the study of emergence has suffered from a lack of formalisms that could be used to guide discussions and advanc...
We investigate the degree to which experiences in three experimental paradigms may arise from phenomenological control, i.e. from the way people can control their experience to meet expectancies and goals. In the experimental situation, expectancies and goals arise from demand characteristics (cues which communicate beliefs about experimental aims...
Predictive coding is an influential model of cortical neural activity. It proposes that perceptual beliefs are furnished by sequentially minimising "prediction errors" - the differences between predicted and observed data. Implicit in this proposal is the idea that perception requires multiple cycles of neural activity. This is at odds with evidenc...
The major theories of consciousness that distinguish conscious from unconscious states can be grouped into two main classes, either higher order or integration theories. There is evidence that different types of mental states can be unconscious, though that conclusion depends on the theory of consciousness assumed. Unconscious memory (in the sense...
Schizophrenia and states induced by certain psychotomimetic drugs may share some physiological and phenomenological properties, but they differ in fundamental ways: one is a crippling chronic mental disease, while the others are temporary, pharmacologically-induced states presently being explored as treatments for mental illnesses. Building towards...
The adaptive regulation of bodily and interoceptive parameters, such as body temperature, thirst and hunger is a central problem for any biological organism. Here, we present a series of simulations using the framework of active inference to formally characterize interoceptive control and some of its dysfunctions. We start from the premise that the...
Bruineberg and colleagues helpfully distinguish between instrumental and ontological interpretations of Markov blankets, exposing the dangers of using the former to make claims about the latter. However, proposing a sharp distinction neglects the value of recognising a continuum spanning from instrumental to ontological. This value extends to the r...
Phenomenological control is the ability to generate experiences to meet expectancies. There are stable trait differences in this ability, as shown by responses to imaginative suggestions of, for example, paralysis, amnesia, and auditory, visual, gustatory and tactile hallucinations. Phenomenological control has primarily been studied within the con...
Emergence is a profound subject that straddles many scientific disciplines, including the formation of galaxies and how consciousness arises from the collective activity of neurons. Despite the broad interest that exists on this concept, the study of emergence has suffered from a lack of formalisms that could be used to guide discussions and advanc...
Reports of changes in experiences of body location and ownership following synchronous tactile and visual stimulation of fake and real hands (rubber hand (RH) effects) are widely attributed to multisensory integration mechanisms. However, existing control methods for subjective report measures (asynchronous stroking and control statements) are conf...
Complex systems, from the human brain to the global economy, are made of multiple elements that interact in such ways that the behaviour of the `whole' often seems to be more than what is readily explainable in terms of the `sum of the parts.' Our ability to understand and control these systems remains limited, one reason being that we still don't...
The Free-Energy-Principle (FEP) is an influential and controversial theory which postulates a deep and powerful connection between the stochastic thermodynamics of self-organization and learning through variational inference. Specifically, it claims that any self-organizing system which can be statistically separated from its environment, and which...
Predictive coding offers a potentially unifying account of cortical function -- postulating that the core function of the brain is to minimize prediction errors with respect to a generative model of the world. The theory is closely related to the Bayesian brain framework and, over the last two decades, has gained substantial influence in the fields...
We introduce a notion of emergence for coarse-grained macroscopic variables associated with highly-multivariate microscopic dynamical processes, in the context of a coupled dynamical environment. Dynamical independence instantiates the intuition of an emergent macroscopic process as one possessing the characteristics of a dynamical system "in its o...
Up to 40% of people report visually evoked auditory responses (vEARs; for example, ‘hearing’ sounds in response to watching silent videos). We investigate the degree to which vEAR experiences may arise from phenomenological control, i.e. from the way people can control their experience to meet expectancies arising from imaginative suggestion. In th...
Reports of experiences of ownership of a fake hand following synchronous tactile and visual stimulation of fake and real hands have been attributed to multisensory integration mechanisms (the rubber hand ‘illusion’). However, it has been shown that the subjective reports expected, namely stronger experiences in the synchronous than asynchronous con...
In a previous paper, we reported substantial relationships between phenomenological control (trait response to imaginative suggestion) and responses to the rubber hand illusion, vicarious pain, and mirror synaesthesia. We argued that these responses may reflect phenomenological control rather than, or in addition to, other mechanisms. Ehrsson et al...
Phenomenological control is the ability to generate experiences to meet expectancies. There are stable trait differences in this ability, as shown by responses to imaginative suggestions of, for example, paralysis, amnesia, and auditory, visual, gustatory and tactile hallucinations. Phenomenological control has primarily been studied within the con...
The exploration-exploitation trade-off is central to the description of adaptive behaviour in fields ranging from machine learning, to biology, to economics. While many approaches have been taken, one approach to solving this trade-off has been to equip or propose that agents possess an intrinsic 'exploratory drive' which is often implemented in te...
The Kalman filter is a fundamental filtering algorithm that fuses noisy sensory data, a previous state estimate, and a dynamics model to produce a principled estimate of the current state. It assumes, and is optimal for, linear models and white Gaussian noise. Due to its relative simplicity and general effectiveness, the Kalman filter is widely use...
The adaptive regulation of bodily and interoceptive parameters, such as body temperature, thirst and hunger is a central problem for any biological organism. Here, we present a series of simulations using the framework of Active Inference to formally characterize interoceptive control and some of its dysfunctions. We start from the premise that the...
Accounts of predictive processing propose that conscious experience is influenced not only by passive predictions about the world, but also by predictions encompassing how the world changes in relation to our actions—that is, on predictions about sensorimotor contingencies. We tested whether valid sensorimotor predictions, in particular learned ass...
The rubber hand illusion (RHI) is a cornerstone of the scientific literature on embodiment. We have recently published a series of studies investigating the RHI, in particular its relationship to hypnotic (imaginative) suggestibility, and the validity of commonly used control conditions. These studies have generated substantial discussion regarding...
Most biological brains, as well as artificial neural networks, are capable of performing multiple tasks [1]. The mechanisms through which simultaneous tasks are performed by the same set of units are not yet entirely clear. Such systems can be modular or mixed selective through some variables such as sensory stimulus [2,3]. Based on simple tasks st...
The broad concept of emergence is instrumental in various of the most challenging open scientific questions—yet, few quantitative theories of what constitutes emergent phenomena have been proposed. This article introduces a formal theory of causal emergence in multivariate systems, which studies the relationship between the dynamics of parts of a s...
Active Inference (AIF) is an emerging framework in the brain sciences which suggests that biological agents act to minimise a variational bound on model evidence. Control-as-Inference (CAI) is a framework within reinforcement learning which casts decision making as a variational inference problem. While these frameworks both consider action selecti...
The theories of consciousness discussed by Doerig and colleagues tend to monolithically identify consciousness with some other phenomenon, process, or mechanism. But by treating consciousness as singular explanatory target, such theories will struggle to account for the diverse properties that conscious experiences exhibit. We propose that progress...
Recent findings have shown that psychedelics reliably enhance brain entropy (understood as neural signal diversity), and this effect has been associated with both acute and long-term psychological outcomes such as personality changes. These findings are particularly intriguing given that a decrease of brain entropy is a robust indicator of loss of...
The recently proposed Activation Relaxation (AR) algorithm provides a simple and robust approach for approximating the backpropagation of error algorithm using only local learning rules. Unlike competing schemes, it converges to the exact backpropagation gradients, and utilises only a single type of computational unit and a single backwards relaxat...
Predictive coding is an influential theory of cortical function which posits that the principal computation the brain performs, which underlies both perception and learning, is the minimization of prediction errors. While motivated by high-level notions of variational inference, detailed neurophysiological models of cortical microcircuits which can...
In hypnotic responding, expectancies arising from imaginative suggestion drive striking experiential changes (e.g., hallucinations) - which are experienced as involuntary - according to a normally distributed and stable trait ability (hypnotisability). Such experiences can be triggered by implicit suggestion and occur outside the hypnotic context....
Prior knowledge has been shown to facilitate the incorporation of visual stimuli into awareness. We adopted an individual differences approach to explore whether a tendency to 'see the expected' is general or method-specific. We administered a binocular rivalry task and manipulated selective attention, as well as induced expectations via predictive...
Can the powerful backpropagation of error (backprop) reinforcement learning algorithm be formulated in a manner suitable for implementation in neural circuitry? The primary challenge is to ensure that any candidate formulation uses only local information, rather than relying on global (error) signals, as in orthodox backprop. Recently several algor...
Grapheme-colour synaesthesia (GCS) is defined by additional perceptual experiences, which are automatically and consistently triggered by specific inducing stimuli. The associative nature of GCS has motivated attempts to induce synaesthesia by means of associative learning. Two recent studies have shown that extensive associative training can gener...
Research has established that prior knowledge of visual stimuli facilitates their entry into awareness. We adopted an individual differences approach to explore whether a tendency to ‘see the expected’ is general or method-specific. We administered a binocular rivalry task and manipulated selective attention, as well as induced expectations via pre...
The field of reinforcement learning can be split into model-based and model-free methods. Here, we unify these approaches by casting model-free policy optimisation as amortised variational inference, and model-based planning as iterative variational inference, within a `control as hybrid inference' (CHI) framework. We present an implementation of C...
Accounts of predictive processing propose that conscious experience is influenced not only by passive predictions about the world, but also by predictions encompassing how the world changes in relation to our actions – that is, on predictions about sensorimotor contingencies. We tested whether valid sensorimotor predictions, in particular learned a...
We first review recent work from our laboratory, which construes hypnotizability as an example of a more general trait of capacity for phenomenological control, which people can use to create subjective experiences in many nonhypnotic contexts where those experiences fulfill people’s goals. Second, we review recent work, which construes phenomenolo...
Active Inference (AIF) is an emerging framework in the brain sciences which suggests that biological agents act to minimise a variational bound on model evidence. Control-as-Inference (CAI) is a framework within reinforcement learning which casts decision making as a variational inference problem. While these frameworks both consider action selecti...
There are several ways to categorise reinforcement learning (RL) algorithms, such as either model-based or model-free, policy-based or planning-based, on-policy or off-policy, and online or offline. Broad classification schemes such as these help provide a unified perspective on disparate techniques and can contextualise and guide the development o...
This short letter is a response to a recent Forum article in Trends in Cognitive Sciences, by Sun and Firestone, which reprises the so-called 'Dark Room Problem' as a challenge to the explanatory value of predictive processing and free-energy-minimisation frameworks for cognitive science. Among many possible responses to Sun and Firestone, we expla...
The extent to which high-level, complex functions can proceed unconsciously has been a topic of considerable debate. While unconscious processing has been demonstrated for a range of low-level processes, from feature integration to simple forms of conditioning and learning, theoretical contributions suggest that increasing complexity requires consc...
Converging theories suggest that organisms learn and exploit probabilistic models of their environment. However, it remains unclear how such models can be learned in practice. The open-ended complexity of natural environments means that it is generally infeasible for organisms to model their environment comprehensively. Alternatively, action-orient...
The broad concept of emergence is instrumental in various of the most challenging open scientific questions -- yet, few quantitative theories of what constitutes emergent phenomena have been proposed. This article introduces a formal theory of causal emergence in multivariate systems, which studies the relationship between the dynamics of parts of...
The central tenet of reinforcement learning (RL) is that agents seek to maximize the sum of cumulative rewards. In contrast, active inference, an emerging framework within cognitive and computational neuroscience, proposes that agents act to maximize the evidence for a biased generative model. Here, we illustrate how ideas from active inference can...
Human perception and experience of time is strongly influenced by ongoing stimulation, memory of past experiences, and required task context. When paying attention to time, time experience seems to expand; when distracted, it seems to contract. When considering time based on memory, the experience may be different than in the moment, exemplified by...
Researchers often adjudicate between models of memory according to the models’ ability to explain impaired patterns of performance (e.g., in amnesia). In contrast, evidence from special groups with enhanced memory is very rarely considered. Here, we explored how people with unusual perceptual experiences (synaesthesia) perform on various measures o...
Many contemporary models of time perception are based on the notion that our brain houses an internal "clock", specialized for tracking duration. Here we show that specialized mechanisms are unnecessary, and that human-like duration judgements can be reconstructed from neural responses during sensory processing. Healthy human participants watched n...
Neuroimaging studies of the psychedelic state offer a unique window onto the neural basis of conscious perception and selfhood. Despite well understood pharmacological mechanisms of action, the large-scale changes in neural dynamics induced by psychedelic compounds remain poorly understood. Using source-localised, steady-state MEG recordings, we de...
In reinforcement learning (RL), agents often operate in partially observed and uncertain environments. Model-based RL suggests that this is best achieved by learning and exploiting a probabilistic model of the world. 'Active inference' is an emerging normative framework in cognitive and computational neuroscience that offers a unifying account of h...
