The organization of distributed neural activity remains one of the central challenges in computational neuroscience. Contemporary frameworks, including Integrated Information Theory, Global Workspace Theory, entropy-based approaches, and electromagnetic field theories, have advanced our understanding of neural coordination but employ different mathematical descriptions of large-scale brain...
Human conscious thought often appears as a diffuse, unstable, and only partly verbalizable field until attention, questioning, decision, or speech stabilizes it into a reportable form. This manuscript develops a quantum-inspired neural framework for that transition. The proposal does not claim that consciousness literally depends on microscopic quantum computation, that the brain implements a...
Along the lines of neuronal global workspace theories, the paper hypothesizes that active neural signal regeneration in recurrent, re-entrant circuits could constitute an organizational basis for states of conscious awareness. In this view, brains are self-production systems that regenerate their own informational, signal states ("neural autopoiesis"). States of awareness themselves depend...
The binding problem and the criticality problem represent two of neuroscience's most persistent challenges: how do distributed neural processes create unified conscious experience, and how does the brain maintain optimal information processing at the critical boundary between order and chaos? This paper argues that both problems emerge from neuroscience's "prickly" bias toward discrete,...
Understanding the neural mechanisms underlying the transitions between different states of consciousness is a fundamental challenge in neuroscience. Thus, we investigate the underlying drivers of changes during the resting-state dynamics of the human brain, as captured by functional magnetic resonance imaging (fMRI) across varying levels of consciousness (awake, light sedation, deep sedation,...
Artificial intelligence (AI) has made some remarkable advances in recent years, particularly within the area of large language models (LLMs) that produce human-like conversational abilities via utilizing transformer-based architecture. These advancements have sparked growing calls to develop tests not only for intelligence but also for consciousness. However, existing benchmarks assess...
As the apparent intelligence of artificial neural networks (ANNs) advances, they are increasingly likened to the functional networks and information processing capabilities of the human brain. Such comparisons have typically focused on particular modalities, such as vision or language. The next frontier is to use the latest advances in ANNs to design and investigate scalable models of...
Introduction Visual-spatial perception is a process for extracting the spatial relationship between objects in the environment. The changes in visual-spatial perception due to factors such as the activity of the sympathetic nervous system (hyperactivation) or parasympathetic nervous system (hypoactivation) can affect the internal representation of the external visual-spatial world. We...
The new approach in cognitive science largely known as "4E cognition" (embodied/embedded/enactive/extended cognition), which sheds new light on the complex dynamics of human consciousness, seems to revive some of Aristotle's views. For instance, the concept of "nature" (phusis) and the discussion on "active intellect" (nous poiêtikos) may be particularly relevant in this respect. Out of the...
Integrated world modeling theory (IWMT) is a synthetic theory of consciousness that uses the free energy principle and active inference (FEP-AI) framework to combine insights from integrated information theory (IIT) and global neuronal workspace theory (GNWT). Here, I first review philosophical principles and neural systems contributing to IWMT's integrative perspective. I then go on to...
Much of current artificial intelligence (AI) and the drive toward artificial general intelligence (AGI) focuses on developing machines for functional tasks that humans accomplish. These may be narrowly specified tasks as in AI, or more general tasks as in AGI - but typically these tasks do not target higher-level human cognitive abilities, such as consciousness or morality; these are left to...
The last decade has witnessed a remarkable progress in our understanding of the brain. This has mainly been based on the scrutiny and modeling of the transmission of activity among neurons across lively synapses. A main conclusion, thus far, is that essential features of the mind rely on collective phenomena that emerge from a willful interaction of many neurons that, mediating other cells,...
The relation between mental states and brain states is important in computational neuroscience, and in psychiatry in which interventions with medication are made on brain states to alter mental states. The relation between the brain and the mind has puzzled philosophers for centuries. Here a neuroscience approach is proposed in which events at the sub-neuronal, neuronal, and neuronal network...
A neuroscience-based approach has recently been proposed for the relation between the mind and the brain. The proposal is that events at the sub-neuronal, neuronal, and neuronal network levels take place simultaneously to perform a computation that can be described at a high level as a mental state, with content about the world. It is argued that as the processes at the different levels of...
The question of whether artificial beings or machines could become self-aware or conscious has been a philosophical question for centuries. The main problem is that self-awareness cannot be observed from an outside perspective and the distinction of being really self-aware or merely a clever imitation cannot be answered without access to knowledge about the mechanism's inner workings. We...
Discrete sequential information coding is a key mechanism that transforms complex cognitive brain activity into a low-dimensional dynamical process based on the sequential switching among finite numbers of patterns. The storage size of the corresponding process is large because of the permutation capacity as a function of control signals in ensembles of these patterns. Extracting...
While functional connectivity networks are often extracted from resting-state fMRI scans, they have been shown to be active during task performance as well. However, the effect of an in-scanner task on functional connectivity networks is not completely understood. While there is evidence that task-evoked positive BOLD response can alter functional connectivity networks, particularly in the...
How the brain reconstitutes consciousness and cognition after a major perturbation like general anesthesia is an important question with significant neuroscientific and clinical implications. Recent empirical studies in animals and humans suggest that the recovery of consciousness after anesthesia is not random but ordered. Emergence patterns have been classified as progressive and abrupt...
Despite the increase of both dynamic and embodied/situated approaches in cognitive science, there is still little research on how coordination dynamics under a closed sensorimotor loop might induce qualitatively different patterns of neural oscillations compared to those found in isolated systems. We take as a departure point the Haken-Kelso-Bunz (HKB) model, a generic model for dynamic...
As a consequence, changes in the external world alter brain organization, which lead to changes in perception and behaviour. However, little is known [2,3] how purely internal, mental states – such as the focus of attention, imagery or meditation – affect behaviour and performance in the absence of external stimulation. The effects of altered external stimulation of the body on somatosensory...
Event Abstract Back to Event A Multi-Scale Analysis to set the Default Mode Network in noisy fMRI data Katherine Baquero1*, Francisco Gómez2, Andrea Soddu2, Audrey Vanhaudenhuyse2, Athena Demertzi2, Jean-Flory Tshibanda3, Olivia Gosseries2, Quentin Noirhomme2, Steven Laureys2 and Eduardo Romero1* 1 National University of Colombia, Biomedical Engineering, Colombia 2 University of Liege,...
In the last few decades several concepts of dynamical systems theory (DST) have guided psychologists, cognitive scientists, and neuroscientists to rethink about sensory motor behavior and embodied cognition. A critical step in the progress of DST application to the brain (supported by modern methods of brain imaging and multi-electrode recording techniques) has been the transfer of its initial...
Behavioral observations suggest that multiple sensory elements can be maintained for a short time, forming a perceptual buffer which fades after a few hundred milliseconds. Only a subset of this perceptual buffer can be accessed under top-down control and broadcasted to working memory and consciousness. In turn, single-cell studies in awake-behaving monkeys have identified two distinct waves of...