RT Journal Article
SR Electronic
T1 The Hallucination Machine: A Deep-Dream VR platform for Studying the Phenomenology of Visual Hallucinations
JF bioRxiv
FD Cold Spring Harbor Laboratory
SP 213751
DO 10.1101/213751
A1 Keisuke Suzuki
A1 Warrick Roseboom
A1 David J. Schwartzman
A1 Anil K. Seth
YR 2017
UL http://biorxiv.org/content/early/2017/11/03/213751.abstract
AB Altered states of consciousness, such as psychotic or pharmacologically-induced hallucinations, provide a unique opportunity to examine the mechanisms underlying conscious perception. However, the phenomenological properties of these states are difficult to isolate experimentally from other, more general physiological and cognitive effects of psychoactive substances or psychopathological conditions. Thus, simulating phenomenological aspects of altered states in the absence of these other more general effects provides an important experimental tool for consciousness science and psychiatry. Here we describe such a tool, the Hallucination Machine. It comprises a novel combination of two powerful technologies: deep convolutional neural networks (DCNNs) and panoramic videos of natural scenes, viewed immersively through a head-mounted display (panoramic VR). By doing this, we are able to simulate visual hallucinatory experiences in a biologically plausible and ecologically valid way. Two experiments illustrate potential applications of the Hallucination Machine. First, we show that the system induces visual phenomenology qualitatively similar to classical psychedelics. In a second experiment, we find that simulated hallucinations do not evoke the temporal distortion commonly associated with altered states. Overall, the Hallucination Machine offers a valuable new technique for simulating altered phenomenology without directly altering the underlying neurophysiology.