The entropic brain: a theory of conscious states informed by neuroimaging research with psychedelic drugs

Abstract

Entropy is a dimensionless quantity that is used for measuring uncertainty about the state of a system but it can also imply physical qualities, where high entropy is synonymous with high disorder. Entropy is applied here in the context of states of consciousness and their associated neurodynamics, with a particular focus on the psychedelic state. The psychedelic state is considered an exemplar of a primitive or primary state of consciousness that preceded the development of modern, adult, human, normal waking consciousness. Based on neuroimaging data with psilocybin, a classic psychedelic drug, it is argued that the defining feature of “primary states” is elevated entropy in certain aspects of brain function, such as the repertoire of functional connectivity motifs that form and fragment across time. Indeed, since there is a greater repertoire of connectivity motifs in the psychedelic state than in normal waking consciousness, this implies that primary states may exhibit “criticality,” i.e., the property of being poised at a “critical” point in a transition zone between order and disorder where certain phenomena such as power-law scaling appear. Moreover, if primary states are critical, then this suggests that entropy is suppressed in normal waking consciousness, meaning that the brain operates just below criticality. It is argued that this entropy suppression furnishes normal waking consciousness with a constrained quality and associated metacognitive functions, including reality-testing and self-awareness. It is also proposed that entry into primary states depends on a collapse of the normally highly organized activity within the default-mode network (DMN) and a decoupling between the DMN and the medial temporal lobes (which are normally significantly coupled). These hypotheses can be tested by examining brain activity and associated cognition in other candidate primary states such as rapid eye movement (REM) sleep and early psychosis and comparing these with non-primary states such as normal waking consciousness and the anaesthetized state.

The Entropy of Laughter: Discriminative Power of Laughter’s Entropy in the Diagnosis of Depression

“…Following [18,19], the brain unifies its information processing by means of a distributed free-energy variable based on the coupling of excitation and inhibition, the informational entropy of which is maximized (optimized) in the ongoing search of adapting the sensory-motor states to the environmental demands. Given the mappings, gradients, circuit topologies, and self-organizing rhythms in the couplings between excitation and inhibition, the blind optimization of this brute "neural entropy" produces the outcome of well-fitted states.…”

“…As will be discussed later on, this difference might indicate two things: that the neural control involved in laughter emission is "more primitive" (clearly, different neural circuits are involved in the control of vowel cords and the whole respiratory-phonatory apparatus); and additionally that an increased entropic distinctiveness of the received laughter may increase its attractiveness and improve the emotional sharing [17]. The theme will also be discussed regarding the interrelationship of neural entropy with the general "stuff" of brain processing [18,19]. About the specific phonation involved, the facial counterparts, the diaphragmatic and bodily movements, and the systemic repercussions (cardiovascular, immune, central and autonomous nervous system, etc.…”

Consciousness: A Molecular Perspective

“…Recently, there has also been a renewed interest in psycho-pharmacology [7]; and also, the role of molecular communication channels in communicating emotions outside of conscious access is currently being investigated [8]. These findings could all be interpreted as indicating molecular mechanisms that are closely related to the phenomenology of consciousness.…”

Waves as the Symmetry Principle Underlying Cosmic, Cell, and Human Languages

“…Carhart-Harris et al [33] a few mm in linear dimensions. When the distances of the signals of individual voxels from the group-mean fMRI signal were calculated and grouped into bins and their frequencies were counted, the histograms shown in Figure 1k were obtained, which fitted PDE.…”