varieties of selflessness

102

150

This is the first in a series of instalments aiming at a minimal model explanation for conscious experience, taking the phenomenal character of “pure consciousness” or “pure awareness” in meditation as its entry point. It develops the concept of “minimal phenomenal experience” (MPE) as a candidate for the simplest form of consciousness, substantiating it by extracting six semantic constraints from the existing literature and using sixteen phenomenological case-studies to incrementally flesh out the new working concept. One empirical hypothesis is that the phenomenological prototype of “pure awareness”, to which all such reports refer, really is the content of a predictive model, namely, a Bayesian representation of tonic alertness. On a more abstract conceptual level, it can be described as a model of an unpartitioned epistemic space.

Section: Case Study #2mentioning

confidence: 99%

Minimal phenomenal experience

Metzinger¹

2020

102

150

“…This would mean that any conscious system (including artificial ones) that can be said to engage in active inference will experience some sort of "mental" agency -generating a new transparent layer in its phenomenal self-model. But this seems to contrast with reports of very vivid phenomenology during otherwise "selfless" experiences (Millière, 2017(Millière, , 2020Saks, 2007).…”

Section: "Self-flattening": the Relationship Between Deep Active Infementioning

confidence: 71%

Attenuating oneself

Limanowski

Friston

2020

In this paper, we address reports of “selfless” experiences from the perspective of active inference and predictive processing. Our argument builds upon grounding self-modelling in active inference as action planning and precision control within deep generative models – thus establishing a link between computational mechanisms and phenomenal selfhood. We propose that “selfless” experiences can be interpreted as (rare) cases in which normally congruent processes of computational and phenomenal self-modelling diverge in an otherwise conscious system. We discuss two potential mechanisms – within the Bayesian mechanics of active inference – that could lead to such a divergence by attenuating the experience of selfhood: “self-flattening” via reduction in the depth of active inference and “self-attenuation” via reduction of the expected precision of self-evidence.

“…Ego-dissolution appears to be induced more reliably under psychedelics than meditation, in a dose-dependent manner, and prompted most reliably by high-doses (Nour et al, 2016). Recent theoretical work has explored the phenomenological and neurophysiological similarities and differences of ego-dissolution induced by drugs and meditation (Millière et al, 2018; see also Limanowski & Friston, 2020, Millière, 2020, Sebastián, 2020 in this special issue).…”

Section: Psychedelicsmentioning

confidence: 99%

Dissolving the self

Deane

2020

Psychedelic drugs such as psilocybin, LSD and DMT are known to induce powerful alterations in phenomenology. Perhaps of most philosophical and scientific interest is their capacity to disrupt and even “dissolve” one of the most primary features of normal experience: that of being a self. Such “peak” or “mystical” experiences are of increasing interest for their potentially transformative therapeutic value. While empirical research is underway, a theoretical conception of the mechanisms underpinning these experiences remains elusive. In the following paper, psychedelic-induced ego-dissolution is accounted for within an active inference framework, as a collapse in the “temporal thickness” of an agent’s deep temporal model, as a result of lowered precision on high-level priors. The argument here is composed of three moves: first, a view of the self-model is proposed as arising within a temporally deep generative model of an embodied organism navigating an affordance landscape in the service of allostasis. Next, a view of the action of psychedelics as lowering the precision of high-level priors within the generative model is unpacked in terms of a high Bayesian learning rate. Finally, the relaxation of high-level priors is argued to cause a “collapse” in the temporal thickness of the generative model, resulting in a collapse in the self-model and a loss of the ordinary sense of being a self. This account has implications for our understanding of ordinary self-consciousness and disruptions in self-consciousness present in psychosis, autism, depression, and dissociative disorders. The philosophical, theoretical and therapeutic implications of this account are touched upon.