A network model of hallucinations

Abstract

The study of hallucinations is complicated by the huge number of factors that determine the occurrence and phenomenological characteristics of these phenomena. Until recently, this has made it impossible to develop a global view of the events that govern their existence. Recent breakthroughs in network science allow for a graphical representation and modeling of large numbers of interacting factors, which may bring such a global view within reach. In this chapter, we will summarize a number of theoretical issues that are required for a basic understanding of network models, and review a number of biochemical and neurophysiological changes that accompany the experience of hallucinations. Collectively, those changes constitute a multitude of factors that give rise to a colorful palette of subjective experiences. Network theory offers a way to integrate those findings in an unprecedented way, by offering a common terminology and methodology to describe relationships between events on different spatial and temporal scales. The specification of network models that incorporate the key players in the production of hallucinations allows researchers to make predictions with respect to specific targets for treatment. At a small spatial scale, new molecular targets are already being identified. At a larger spatial scale, network simulations may allow for a more specific targeting of brain areas using techniques that alter brain function, such as transcranial magnetic stimulation, electrocortical stimulation, and deep brain stimulation. With the progression of knowledge and the use of integrative science, it is hoped that a bigger arsenal of treatment options will become available for hallucinations and other psychotic symptoms in the foreseeable future.