Consciousness seminars

Sleep is classically presented as an all-or-nothing phenomenon. Yet, there is increasing evidence showing that sleep and wakefulness can actually intermingle and that wake-like and sleep-like activity can be observed concomitantly in different brain regions. I will here explore the implications of this conception of sleep as a local phenomenon for cognition and consciousness. In the first part of my presentation, I will show how local modulations of sleep depth during sleep could support the processing of sensory information by sleepers. I will also how, under certain circumstances, sleepers can learn while sleeping but also how they can forget. In the second part, I will show how the reverse phenomenon, sleep intrusions during waking, can explain modulations of attention. I will focus in particular on modulations of subjective experience and how the local sleep framework can inform our understanding of everyday phenomena such as mind wandering and mind blanking. Through this presentation and the exploration of both sleep and wakefulness, I will seek to connect changes in neurophysiology with changes in behaviour and subjective experience.

In this talk, I’ll introduce the formal concept of a (pre)sheaf as data attached to a topological space. Sheaves capture the notion of patching local sources of information to form a global whole, e.g., the binding of visual features such as colour and shape. The formal theory appears to be closely related to the foundational properties asserted by the Information Integration Theory (IIT) for phenomenology. A comparison is intended to engender discussion on ways that phenomenology may benefit from a sheaf theory, or (more generally) a category theory approach.

Neuroscientific methods successfully account for a system’s functional properties, but leave out the subjective properties of the accompanying experience. According to IIT, phenomenology can be studied scientifically by unfolding the cause-effect structure specified by a system. To illustrate how, in this talk I compare two systems (a grid and a map) to show that they can be functionally equivalent in performing fixation, but only one can specify a cause-effect structure that accounts for the extendedness of phenomenal space.

It is generally agreed upon that qualities of conscious experience instantiate structural properties, usually called relations. They furnish a representation of qualities (or qualia, in fact) in terms of a mathematical space Q (rather than a set), which is crucial to both modelling and measuring of conscious experience." "What is usually disregarded is that “only such structural properties generalize across individuals” (Austen Clark), but that qualities themselves as differentiated by stimulus specifications, behavior or reports do not. We show that this implies that only the part of Q which is invariant with respect to the automorphism group has a well-defined referent, while individual elements do not. This poses a prima facie limitation of any theory or experiment that aims to address individual qualities. We show how mathematical theories of consciousness can overcome this limitation via symmetry groups and group actions, making accessible to science what is properly called private language.

Category theory is a branch of mathematics which have been used to organize various regions of mathematics and related sciences from a radical “relation-first” point of view. Why consciousness researchers should care about category theory? " "There are (at least) 3 reasons:" "1 Everything is relational" "2 Everything is relation" "3 Relation is everything" "In this talk we explain the reasons above more concretely and introduce the ideas to utilize basic concepts in category theory for consciousness studies.

The tight relationship between attention and conscious perception has been extensively researched in the past decades. However, whether attentional modulation extended to unconscious processes remained largely unknown, particularly when it came to abstract and high-level processing. I will talk about a recent study where we utilized the Stroop paradigm to show that task load gates unconscious semantic processing. In a series of psychophysical experiments, the unconscious word semantics influenced conscious task performance only under the low task load condition, but not the high task load condition. Intriguingly, with enough practice in the high task load condition, the unconscious effect reemerged. These findings suggest a competition of attentional resources between unconscious and conscious processes, challenging the automaticity account of unconscious processing.

In this talk, I shall not argue for any single thesis or theory in the realm of the (un)consciousness and (in)attention. Instead I will discuss specific examples where philosophers and psychologists can have genuine collaborations in this area. Since issues concerning phenomenological overflow is already too familiar for this audience, I will briefly discuss it only, and focus on other issues that have not been overworked. The exact contents are to be determined, but I will perhaps focus on recent controversies over “sustained representation of perspectival shape” (Morales, Bax, and Firestone, 2020, 2021).

I will discuss the mechanisms that determine whether a weak visual stimulus will reach consciousness or not. If the stimulus is simple, early visual cortex acts as a relay station that sends the information to higher visual areas. If the stimulus arrives at a minimal strength, it will be stored in working memory and can be reported. However, during more complex visual perceptions, which for example depend on the segregation of a figure from the background, early visual cortex’ role goes beyond a simply relay. It now acts as a cognitive blackboard and conscious perception depends on it. Our results inspire new approaches to create a visual prosthesis for the blind, by creating a direct interface with the visual brain. I will discuss how high-channel-number interfaces with the visual cortex might be used to restore a rudimentary form of vision in blind individuals.

In this talk he will present current work in progress on “irruption theory”, a new theory of consciousness that integrates an embodied-enactive account of basic mind with radical formulations of the freedom and efficacy of intentional agency.

Where in the brain consciousness resides remains unclear. It has been suggested that the subnetworks supporting consciousness should be bidirectionally (recurrently) connected because both feed-forward and feedback processing are necessary for conscious experience. Accordingly, evaluating which subnetworks are bidirectionally connected and the strength of these connections would likely aid the identification of regions essential to consciousness. Here, we propose a method for hierarchically decomposing a network into cores with different strengths of bidirectional connection, as a means of revealing the structure of the complex brain network. We applied the method to a whole-brain mouse connectome. We found that cores with strong bidirectional connections consisted of regions presumably essential to consciousness (e.g., the isocortical and thalamic regions, and claustrum) and did not include regions presumably irrelevant to consciousness (e.g., cerebellum). Contrarily, we could not find such correspondence between cores and consciousness when we applied other simple methods which ignored bidirectionality. These findings suggest that our method provides a novel insight into the relation between bidirectional brain network structures and consciousness. Our recent preprint on this work is here: https://doi.org/10.1101/2021.07.12.452022.

Tom Froese is Assistant Professor at the Okinawa Institute of Science and Technology Graduate University (OIST), where he heads the Embodied Cognitive Science Unit. He is a cognitive scientist with a background in phenomenological philosophy, human-computer interaction, and complex systems theory. His interdisciplinary research centers on the role of agent-environment interaction in shaping cognition and consciousness, specifically when the interaction process involves sociality and technology. In this talk he will present current work in progress on “irruption theory”, a new theory of consciousness that integrates an embodied-enactive account of basic mind with radical formulations of the freedom and efficacy of intentional agency.

The brain is a prediction machine. Yet the world is never entirely predictable, for any animal. Unexpected events are surprising and this typically evokes prediction error signatures in animal brains. In humans such mismatched expectations are often associated with an emotional response as well. Appropriate emotional responses are understood to be important for memory consolidation, suggesting that valence cues more generally constitute an ancient mechanism designed to potently refine and generalize internal models of the world and thereby minimize prediction errors. On the other hand, abolishing error detection and surprise entirely is probably also maladaptive, as this might undermine the very mechanism that brains use to become better prediction machines. This paradoxical view of brain functions as an ongoing tug-of-war between prediction and surprise suggests a compelling new way to study and understand the evolution of consciousness in animals. I will present approaches to studying attention and prediction in the tiny brain of the fruit fly, Drosophila melanogaster. I will discuss how an ‘active’ sleep stage (termed rapid eye movement – REM – sleep in mammals) may have evolved in the first animal brains as a mechanism for optimizing prediction in motile creatures confronted with constantly changing environments. A role for REM sleep in emotional regulation could thus be better understood as an ancient sleep function that evolved alongside selective attention to maintain an adaptive balance between prediction and surprise. This view of active sleep has some interesting implications for the evolution of subjective awareness and consciousness.

Agent-causal libertarian free will asserts that the conscious agent is the ultimate cause of her own voluntary behavior. A major reason to reject libertarian free will is that it seems incompatible with our current knowledge of physics. In this talk I will argue how quantum processes, specifically non-random collapses of the wavefunction in the human cortex, may enable libertarian free will. I will discuss how this account can be empirically tested.

Over the last fifteen years, Simona Ginsburg and I developed an evolutionary approach for studying basic consciousness, suggesting that the evolution of learning drove the evolutionary transition to from non-conscious to conscious animals. I present the rationale underlying this thesis, which has led to the identification of a capacity that we call the evolutionary transition marker, which, when we find evidence of it, we have evidence that the major evolutionary transition in which we are interested has gone to completion. I then put forward our proposal that the evolutionary marker of basic consciousness is a complex form of associative learning that we call unlimited associative learning (UAL), and that the evolution of this capacity drove the transition to consciousness. I discuss the implications of this thesis for questions pertaining to the neural dynamics that constitute conscious, to its taxonomic distribution and to the ecological context in which it first emerged. I end by pointing to some of the ways in which the relationship between UAL and consciousness can be experimentally tested in humans and in non-human animals.

The study of altered states of consciousness has long had the potential to provide important insight into the nature of consciousness. In recent years there has been a resurgence of research and public interest in atypical or altered states of consciousness. These have focused both on conditions in which consciousness is considered to be impaired due to brain trauma or enhanced in some way through mediation practices or ingestion of psychedelics. The talk will begin with a brief overview of recent scientific approaches to understanding these different types of altered consciousness. The remainder of the talk will focus on lab-based experiments conducted by myself and others looking at the effects of serotoninergic hallucinogens (i.e. psilocybin and LSD) on perceptual and cognitive function. Together this body of research provides important new insights for the scientific study of consciousness and an initial understanding of the neuropharmacological mechanisms underlying conscious experience.

The cognitive neuroscience of conscious perception has seen considerable growth over the past few decades. Confirming an influential hypothesis driven by earlier studies of neuropsychological patients, we have found that the lateral and polar prefrontal cortices play important causal roles in the generation of subjective experiences. However, this basic empirical finding has been hotly contested by researchers with different theoretical commitments, and the differences are at times difficult to resolve. To address the controversies, I suggest one alternative venue may be to look for clinical applications derived from current theories. I outline an example in which we used closed-loop fMRI combined with machine learning to nonconsciously manipulate the physiological responses to threatening stimuli, such as spiders or snakes. A clinical trial involving patients with phobia is currently taking place. I also outline how this theoretical framework may be extended to other diseases. Ultimately, a truly meaningful understanding of the fundamental nature of our mental existence should lead to useful insights for our colleagues on the clinical frontlines. If we use this as a yardstick, whoever loses the esoteric theoretical debates, both science and the patients will always win.

In recent years, artificial neural networks have demonstrated human-like or super-human performance in many tasks including image or speech recognition, natural language processing (NLP), playing Go, chess, poker and video-games. One remarkable feature of the resulting models is that they can develop very intuitive latent representations of their inputs. In these latent spaces, simple linear operations tend to give meaningful results, as in the well-known analogy QUEEN-WOMAN+MAN=KING. We postulate that human brain representations share essential properties with these deep learning latent spaces. To verify this, we test whether artificial latent spaces can serve as a good model for decoding brain activity. We report improvements over state-of-the-art performance for reconstructing seen and imagined face images from fMRI brain activation patterns, using the latent space of a GAN (Generative Adversarial Network) model coupled with a Variational AutoEncoder (VAE). With another GAN model (BigBiGAN), we can decode and reconstruct natural scenes of any category from the corresponding brain activity. Our results suggest that deep learning can produce high-level representations approaching those found in the human brain. Finally, I will discuss whether these deep learning latent spaces could be relevant to the study of consciousness.

I will discuss the mechanisms that determine whether a weak visual stimulus will reach consciousness or not. If the stimulus is simple, early visual cortex acts as a relay station that sends the information to higher visual areas. If the stimulus arrives at a minimal strength, it will be stored in working memory. However, during more complex visual perceptions, which for example depend on the segregation of a figure from the background, early visual cortex’ role goes beyond a simply relay. It now acts as a cognitive blackboard and conscious perception depends on it. Our results also inspire new approaches to create a visual prosthesis for the blind, by creating a direct interface with the visual cortex. I will discuss how high-channel-number interfaces with the visual cortex might be used to restore a rudimentary form of vision in blind individuals.