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David J. Schwartzman

University of Sussex

7 papers in the library · 54 citations · publishing 2017-2026

Papers

Increased spontaneous EEG signal diversity during stroboscopically-induced altered states of consciousness

bioRxiv (Cold Spring Harbor Laboratory) January 4, 2019 David J. Schwartzman, Michael Schartner, Benjamin B. Ador et al. 31 citations preprint

Stroboscopic stimulation—flashing light—can induce altered states of consciousness without drugs, increasing the intensity and range of subjective experiences, including simple and complex visual hallucinations. These experiences were accompanied by rises in EEG signal diversity, measured by Lempel-Ziv complexity, that exceeded levels seen during wakeful rest. The results align with previous findings from psychedelic studies and support the idea that neural signal diversity reflects the richness of subjective experience across different states of consciousness.

Modelling phenomenological differences in aetiologically distinct visual hallucinations using deep neural networks

Frontiers in Human Neuroscience January 3, 2024 Keisuke Suzuki, Anil K. Seth, David J. Schwartzman 20 citations

Visual hallucinations differ substantially depending on their cause, such as neurodegenerative disease, visual loss, or psychedelic drugs. Using a deep neural network approach called computational (neuro)phenomenology, researchers identified three key dimensions that distinguish these hallucinations: realism (how true-to-life they seem), spontaneity (how much they depend on sensory input), and complexity. By tuning the network along these dimensions, they generated synthetic hallucinations characteristic of each cause. Two studies with patients having Parkinson's disease, Lewy body dementia, or Charles Bonnet syndrome, and people with recent psychedelic experience, confirmed that these synthetic images matched the phenomenology reported by each group. The findings show that a neural network model can capture the distinctive visual features of hallucinations from different origins.

The Hallucination Machine: A Deep-Dream VR platform for Studying the Phenomenology of Visual Hallucinations

bioRxiv Preprint Server November 3, 2017 Keisuke Suzuki, Warrick Roseboom, David J. Schwartzman et al. 2 citations preprint

A tool called the Hallucination Machine simulates visual hallucinatory experiences using deep convolutional neural networks and panoramic virtual reality videos of natural scenes. It induces visual phenomenology qualitatively similar to classical psychedelics, but does not evoke the temporal distortion commonly associated with altered states. This technique allows researchers to study altered consciousness without the confounding physiological and cognitive effects of psychoactive substances or psychopathological conditions, offering a valuable method for consciousness science and psychiatry.

A Large-Scale Computer-Vision Mapping of the Geometric Structures of Stroboscopically-Induced Visual Hallucinations

bioRxiv (Cold Spring Harbor Laboratory) February 18, 2026 Ethan Grove, Trevor Hewitt, Anil K. Seth et al. 1 citation

Visual hallucinations (VHs) occur in psychedelic states and various psychiatric and neurological conditions, but their phenomenology is hard to characterize due to a lack of large-scale datasets. Stroboscopic light stimulation (SLS) with closed eyes reliably induces VHs in healthy people, producing vivid colors and dynamic geometric patterns similar to simple VHs in other contexts. Researchers developed an unsupervised computer-vision pipeline to analyze 10,598 drawings made after hallucination-inducing SLS at a public installation. Most drawings contained geometric forms, consistent with prior observations, but novel patterns like concentric squares, crosses, and hyperbolic shapes also appeared. The pipeline organized the drawings into interpretable classes, mapping the diversity of simple geometric VHs and placing new constraints on theoretical accounts.

Stroboscopically Induced Visual Hallucinations: Historical, Phenomenological and Neurobiological Perspectives

December 13, 2024 Trevor Hewitt, Ioanna Amaya, Romy Beauté et al. preprint

Exposure to rapid and bright stroboscopic light can induce vivid visual hallucinations of color and geometric forms, a phenomenon first documented by Purkinje over 200 years ago. Despite centuries of scientific, therapeutic, and cultural interest, fundamental questions remain about its phenomenology, physiological origins, and potential clinical applications. This narrative review summarizes the historical research on stroboscopic light stimulation, its use in recreational and lay-therapeutic settings, and discusses the phenomenology of these experiences. It also examines current perspectives on the neural mechanisms that may underlie stroboscopically induced experiences and outlines directions for future research.

Stroboscopic Light Stimulation in Adults Reporting Depressive Symptoms: Safety, Tolerability, Feasibility, and Active-Comparator Development in a Staged Early-Phase Study

medRxiv Preprint Server June 17, 2026 Danny Nacker, Luise Kalus, Anil K. Seth et al. preprint

Supervised stroboscopic light stimulation (SLS) was safe, tolerable, and feasible in adults with depressive symptoms, but efficacy was not established. In a staged program, 31 participants tested 11 SLS parameter sets; no severe adverse reactions occurred, and mean discomfort was low (0.49 out of 10). A subsequent randomized trial assigned 84 participants to four weekly 31-minute sessions of SLS or a low-phenomenology control. Retention was 83.3% (70 of 84 participants), with higher retention in the intervention arm (39 of 42) than the control arm (31 of 42). Exploratory depressive-symptom changes suggested a possible signal on the BDI-II but do not confirm efficacy. The next step is a Phase 2a feasibility trial with a locked protocol.

Mapping of Subjective Accounts into Interpreted Clusters (MOSAIC): Topic Modelling and LLM applied to Stroboscopic Phenomenology

arXiv Preprint Archive February 25, 2025 Romy Beauté, David J. Schwartzman, Guillaume Dumas et al.

Stroboscopic light stimulation on closed eyes typically induces simple visual hallucinations—vivid, geometric, and colorful patterns. An analysis of 862 open-ended reports from the Dreamachine immersive experience, using large language models and topic modeling, confirmed these simple hallucinations and also revealed altered states of consciousness and complex hallucinations. This computational approach enables systematic study of subjective experiences beyond standard questionnaires, capturing subtle patterns not readily identified through closed-form questions. The findings broaden understanding of stroboscopically induced phenomena and demonstrate the potential of natural language processing in computational neurophenomenology.