@Aidan Lyon
Editorial for special issue of Philosophical Psychology on the “Mystical Entropy” project
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We can't see it, but we're all trapped inside these strange repeating loops.
— Morpheus, Matrix 4
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The idea that psychedelics transform the mind by loosening rigid structures is one of the oldest intuitions in psychedelic science. It was central to psycholytic therapy in the 1950s (e.g., Sandison 1954)—indeed, psycholytic literally means “mind-loosening” (Sessa 2016)—and it remains influential today.
In recent decades, this intuition received a neuroscientific formulation in the entropic brain hypothesis (EBH), according to which psychedelics increase brain entropy, loosening entrenched neural patterns and opening space for more adaptive ones to form (Carhart-Harris et al. 2014; Carhart-Harris 2018). The EBH has had a substantial impact on the literature, but “brain entropy” has proven difficult to define precisely. Different entropy metrics yield heterogeneous and only weakly correlated results (e.g., McCulloch et al. 2023; Lewis-Healey et al. 2024), suggesting that “brain entropy” may not track a unified phenomenon, and the relation between neural entropy and subjective experience remains philosophically unclear (Letheby 2021).
The Mystical Entropy project approaches this problem as one of conceptual clarification with empirical implications. Instead of defining brain entropy directly from neuroimaging, it asks what the corresponding notion of mental entropy might be, and whether greater philosophical precision about entropy can illuminate psychedelic transformation. To pursue that question, it turns to contemplative and mystical traditions—not as sources of ready-made theory, but as disciplined domains in which processes of dissolution, release, and reorganization have long been explored from the first-person point of view. The hope is that, by thinking more carefully about entropy in light of such traditions, we can sharpen and systematize the conceptual tools of psychedelic science.
One result of this inquiry is especially important for the present editorial. The concept of entropy, as used in science, divides into two importantly different notions that are often run together: entropy as uncertainty in information theory and entropy as disorder in thermodynamics (Frigg & Werndl 2011; Ben-Naim 2020). These notions do not merely differ in formal definition; they track different kinds of process. In the information-theoretic sense, entropy measures uncertainty and thus the degree to which a system is unconstrained or unpredictable. In the thermodynamic sense, entropy concerns the transformation and dispersion of energy, and the limits this places on the conversion of potential into organized work.
This distinction extends beyond physics and information theory. It aligns with a structural polarity that recurs across contemplative traditions: between orientations of stillness, openness, and dissolution, and orientations of energy, embodiment, and transformation—what Lyon and Vaidya (2026) term Shiva and Shakti, following yogic tradition. Contemporary psychedelic science has developed the Shiva side extensively, most prominently through its focus on mystical experience as a central construct. Experiences of unity and dissolution—operationalized psychometrically and linked to therapeutic outcome—capture this dimension of loosening and unbinding. Yet much of psychedelic transformation remains underdescribed: mystical experience, while robustly correlated with therapeutic outcome, explains only part of the variance, leaving a substantial remainder—the so-called “dark matter” of psychedelic science (cf. Taves 2020; Kangaslampi 2023; Wolff et al. 2024; Yaden et al. 2024; Romeo et al. 2025; Lyon & Vaidya 2026). What remains under-theorized is the Shakti side: the energetic, embodied, and formative dimensions of these states—where “energy” is understood functionally as patterns of activation across affect, attention, and embodiment—through which experience is reorganized into new patterns of thought, feeling, and behavior. Given the success of Shiva-oriented models (cf. Stace 1961; Pahnke and Richards 1966; Griffiths et al. 2016), there is good reason to expect comparable gains from developing this dimension.
This editorial argues that both the thermodynamic conception of entropy and the Shakti side of mysticism have been comparatively neglected in psychedelic science, and that recovering them opens a powerful new research program. The core parallel is straightforward: thermodynamics concerns making engines fuel-efficient, while Shakti-oriented traditions—loosely known as Tantra—concern making the human system prana-efficient. Both address the problem of converting potential into actual energy while minimizing waste. Thermodynamics studies external, “physical” energy; Tantra concerns internal, “subtle” energy. Taken together, this suggests that Tantric traditions such as Kundalini Yoga may help psychedelic science better understand and wield the psychic energy unleashed by psychedelics. On this basis, Lyon and Vaidya (2026) propose the Psychedelic–Kundalini Thesis (PKT): that the energetic effects of psychedelics can be systematically understood through the conceptual framework of Kundalini Yoga, yielding predictions at the phenomenological, neuroscientific, and therapeutic levels (cf. Grof 1975; Sannella 1976; DeGracia 1997; Corneille & Luke 2021).
The paper proceeds as follows. Section 2 distinguishes the two concepts of entropy. Section 3 shows how they map onto the polarity of Shiva and Shakti. Section 4 argues that psychedelic science has largely developed the Shiva side while neglecting the Shakti side. Section 5 presents the PKT and its phenomenological, neuroscientific, and therapeutic implications. Section 6 introduces the PEACE framework for building and evaluating such maps, and for reading the other contributions to this special issue. I conclude with a reflection on what it takes to be liberated from our strange repeating loops.
The term "entropy" carries two distinct scientific meanings that are routinely conflated — a confusion that Arieh Ben-Naim (2020) has called the Greatest Blunder in the History of Science. The conflation is consequential: it obscures the fact that entropy as uncertainty and entropy as disorder track fundamentally different kinds of process, with different implications for how we understand psychedelic transformation.
The confusion can be traced to Shannon’s 1948 formulation of information theory. In developing his mathematical theory of communication (which later came to be known as “information theory”), Shannon needed a name for the central quantity in his framework. He considered calling it “information,” but the term was already overused, and he leaned instead toward “uncertainty.” In discussion with John von Neumann, however, a different suggestion emerged: “You should call it entropy, for two reasons. In the first place your uncertainty function has been used in statistical mechanics under that name, so it already has a name. In the second place, and more important, no one really knows what entropy really is, so in a debate you will always have the advantage” (Tribus and McIrvine 1971). Shannon accepted the suggestion, and the ambiguity has persisted ever since.
This persistence is not merely a historical artifact of naming. As philosophers of physics have emphasized, even within thermodynamics and statistical mechanics there is no single unproblematic conception of entropy, but a family of related and partly competing notions (Sklar 1993; Uffink 2001). The von Neumann remark is thus not just a witticism, but a reflection of a deeper conceptual instability.
We begin with the conception of entropy that arises in information theory, where the central problem is not meaning but communication under conditions of noise. In Claude Shannon’s original formulation, a sender transmits a message through an imperfect channel, and the receiver must infer what was sent from a potentially distorted signal. The question is how uncertain the receiver is about the original message, and how that uncertainty can be quantified.
Shannon’s key insight was that this uncertainty can be modeled using probability theory. Given a set of possible messages and their probabilities, one can define a measure of the receiver’s overall uncertainty—what Shannon called “entropy”. This is not a property of any particular outcome, but of the distribution over possibilities. A system has low entropy when probability is concentrated on a few possible outcomes, and high entropy when it is spread across many. Entropy thus measures how constrained or unconstrained the space of possibilities is.