Psychedelics and EEG-Derived Measures of Brain Entropy
The brain is a dynamic system that constantly balances order and disorder reflected in hyper and hypoconnectivity of networks. Too much rigidity, and thought becomes repetitive, compulsive, or depressed. Too much chaos, and coherent experience dissolves. Psychedelics tilt this balance.
The Entropic Brain Hypothesis, developed by neuroscientist Robin Carhart-Harris and colleagues, frames this shift in terms of entropy or the randomness and variability of neural activity. In normal waking life, the brain sits in a “slightly subcritical” regime: organized enough for stable reasoning, constrained enough to filter the flood of sensory inputs. Under anesthesia, deep sleep, or coma, entropy falls sharply. But in the psychedelic state, entropy rises. The system explores more possible brain states, becoming more fluid, less predictable, and more open to novelty.
Increased Network Entropy – Increased Repertoire of States
When we record EEG during a psychedelic state, we can measure the change in entropy in real time. As a result, the Default Mode Network (DMN) - the midline system that keeps our internal story coherent - begins to loosen. At the same time, other networks that are usually segregated ‘get the message’ to start rewiring in new and unpredictable ways. Neurons start to physically form new connections on their terminals.
This expansion of the brain’s state repertoire can be captured directly with EEG entropy measures. Metrics related to signal complexity quantify how diverse and unpredictable the signal becomes, showing that under psychedelics the brain visits more states, or a loosening of the “self-model.”
Mechanism at the Receptor Level
The pivot point lies in 5-HT2A receptors, concentrated in high-level cortical regions. Psychedelics activate these neurons, producing cascades that destabilize the current state. The DMN loses its dominance; hidden pathways light up. From the standpoint of predictive coding, entrenched priors relax and the brain becomes more entropic.
Recent research has focused on isolating the therapeutic neuroplastogen effects of psychedelics from their hallucinogenic properties, as well as investigating how therapeutic effects (e.g., on depression) are mediated by downstream pathways that lead to neuroplasticity with increased number of possible connections.
Clinical Implications
What does this mean for therapy? Many psychiatric disorders can be seen as disorders of rigidity, i.e., brains stuck in narrow states (or ‘attractors’). Depression, OCD, PTSD: different syndromes, but each marked by reduced network flexibility.
When psychedelics temporarily push the brain into a higher-entropy regime, it is a chance to reset. In structured therapeutic contexts, patients often report the emergence of new perspectives, the breaking of loops, the ability to reframe entrenched narratives.
EEG-derived entropy quantifies whether a patient’s brain has entered a higher-entropy state during treatment, and additional network connectivity metrics show whether that shift is accompanied by a reorganization of network connectivity. Over repeated sessions, entropy and connectivity measures could help determine not only that a reset occurred, but also whether the new network configuration stabilizes into a healthier, more flexible state.
In clinical practice, this becomes a tool for assessing treatment response, tailoring protocols, and distinguishing transient disruption from durable therapeutic change.
Why It Matters for Drug Development
For drug developers, entropy can be a measurable biomarker, accessible with quantitative EEG. Entropy metrics, together with network connectivity measures, can be used in several concrete ways:
Screening compounds for neuroplastic potential and long-term effects: An acute increase in EEG entropy indicates that the brain has shifted into a more flexible state. When combined with connectivity analyses, it becomes possible to not only confirm that the shift occurred, but also to characterize the new network configuration and assess its stability over time. This allows investigators to track whether a compound produces transient disruption alone, or whether it supports the establishment of a reorganized and durable network state.
Guiding dose selection: Entropy provides a quantitative, dose-responsive signal. Tracking entropy shifts in EEG enables the identification of effective doses that produce measurable network-level effects within a safety range.
Developing dynamic biomarkers: Because entropy reflects both receptor-level activation and the resulting network reconfiguration, it can serve as a translational biomarker linking molecular pharmacology to systems-level remodeling.
In this way, EEG-derived entropy measures provide a bridge between receptor pharmacology and therapeutic transformation, offering a quantitative framework for further advances in the psychedelic space.