Computational modeling of the temporal influences between cues, craving and use in addiction: a dynamical system analysis based on ecological momentary assessment data.

Substance Use Disorders (SUD) can be conceptualized as a prospective link from cues to craving and use. To explore the nonlinear relationships between craving and cues, this study applied dynamical systems theory (DST) to ecological momentary assessment (EMA) data. Optimized linear Seasonal Auto-Regressive Integrated Moving Average with eXogenous variable (SARIMAX) models were used to phenotype patients with SUD (alcohol, tobacco, cannabis, opiates, and cocaine), considering the potential for complex interactions between cue exposure and craving intensity in daily life. These phenotypic profiles were replicated in computational DST models to analyze the nonlinear interactions between cues, craving, and use. The study involved 211 individuals and 8260 observations, with 154 patients fitting the SARIMAX model for the influence of cues on craving, and 57 patients fitting the SARIMAX model for a possible influence of craving on cues. Two DST models were adjusted to replicate the complex temporal dynamics of SUD based on these two directions of influence. The first DST model (adjusted to the influence of cues on craving) showed that an increase in cues leads to a rise in craving, which then diminishes both cues and craving itself, with use patterns following craving's trajectory. This patient profile is driven by a phenomenon of "maximum cue saturation". The second DST model (adjusted to the influence of craving on cues) demonstrated that an increase in craving was followed by an increase in cue reporting, leading to use, with use peaking and then craving droping. This patient profile is characterized by a phenomenon of "maximum use saturation". Both models highlight craving as an essential modulator between cues and use, opening new therapeutic avenues.