Anil K Seth

Anil K Seth
University of Sussex · Sackler Centre for Consciousness Science (SCCS)

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298
Publications
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Publications

Publications (298)
Article
Full-text available
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...
Article
Full-text available
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...
Article
Full-text available
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...
Article
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...
Preprint
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...
Preprint
Full-text available
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...
Article
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...
Preprint
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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...
Article
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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...
Preprint
Full-text available
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...
Article
Full-text available
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...
Preprint
Full-text available
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...
Preprint
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...
Preprint
Full-text available
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...
Preprint
Full-text available
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...
Preprint
Full-text available
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...
Preprint
Full-text available
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...
Preprint
Full-text available
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...
Article
Full-text available
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...
Article
Full-text available
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...
Chapter
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...
Article
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...
Preprint
Full-text available
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...
Preprint
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...
Preprint
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...
Article
Full-text available
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....
Article
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...
Preprint
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...
Preprint
Full-text available
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...
Preprint
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...
Preprint
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...
Preprint
Full-text available
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...
Preprint
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...
Preprint
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...
Preprint
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...
Preprint
Full-text available
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...
Article
Full-text available
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...
Preprint
Full-text available
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...
Preprint
Full-text available
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...
Preprint
Full-text available
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...
Article
Full-text available
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...
Preprint
Full-text available
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...
Article
People with synaesthesia have additional perceptual experiences, which are automatically and consistently triggered by specific inducing stimuli. Synaesthesia therefore offers a unique window into the neurocognitive mechanisms underlying conscious perception. A long-standing question in synaesthesia research is whether it is possible to artificiall...
Article
Full-text available
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...
Preprint
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...
Article
Full-text available
The neural basis of time perception remains unknown. A prominent account is the pacemaker-accumulator model, wherein regular ticks of some physiological or neural pacemaker are read out as time. Putative candidates for the pacemaker have been suggested in physiological processes (heartbeat), or dopaminergic mid-brain neurons, whose activity has bee...
Preprint
Full-text available
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...
Preprint
Full-text available
Most information dynamics and statistical causal analysis frameworks rely on the common intuition that causal interactions are intrinsically pairwise -- every 'cause' variable has an associated 'effect' variable, so that a 'causal arrow' can be drawn between them. However, analyses that depict interdependencies as directed graphs fail to discrimina...
Preprint
Full-text available
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...
Article
Full-text available
We investigated differences in intentional binding in high and low hypnotizable groups to explore two questions relating to (a) trait differences in the availability of motor intentions to metacognitive processes and (b) a proposed cue combination model of binding. An experience of involuntariness is central to hypnotic responding and may arise fro...
Article
The experience of authorship over one’s actions and their consequences—sense of agency—is a fundamental aspect of conscious experience. In recent years, it has become common to use intentional binding as an implicit measure of the sense of agency. However, it remains contentious whether reported intentional-binding effects indicate the role of inte...
Preprint
[Published in Nature Communications as Trait phenomenological control predicts experience of mirror synaesthesia and the rubber hand illusion] The control of top down processes to generate experience has been studied within the context of hypnosis since the birth of psychological science. In hypnotic responding, expectancies arising from imaginativ...
Preprint
Neural processes in the brain operate at a range of temporal scales. Granger causality, the most widely-used neuroscientific tool for inference of directed functional connectivity from neurophsyiological data, is traditionally deployed in the form of one-step-ahead prediction regardless of the data sampling rate, and as such yields only limited ins...
Article
To investigate how embodied sensorimotor interactions shape subjective visual experience, we developed a novel combination of Virtual Reality (VR) and Augmented Reality (AR) within an adapted breaking continuous flash suppression (bCFS) paradigm. In a first experiment, participants manipulated novel virtual 3D objects, viewed through a head-mounted...
Article
Full-text available
Tourette syndrome is a hyperkinetic movement disorder. Characteristic features include tics, recurrent movements that are experienced as compulsive and “unwilled”; uncomfortable premonitory sensations that resolve through tic release; and often, the ability to suppress tics temporarily. We demonstrate how these symptoms and features can be understo...
Article
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The phenomenon of change blindness reveals that people are surprisingly poor at detecting unexpected visual changes; however, research on individual differences in detection ability is scarce. Predictive processing accounts of visual perception suggest that better change detection may be linked to assigning greater weight to prediction error signal...
Article
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Despite being a fundamental dimension of experience, how the human brain generates the perception of time remains unknown. Here, we provide a novel explanation for how human time perception might be accomplished, based on non-temporal perceptual classification processes. To demonstrate this proposal, we build an artificial neural system centred on...
Preprint
Full-text available
What are the global neuronal signatures of altered states of consciousness (ASC)? Recently, increases in neural signal diversity, compared to those found in wakeful rest, have been reported during psychedelic states. Neural signal diversity has previously been identified as a robust signature of the state of consciousness, showing lower scores duri...