title: Neural network model of prepulse inhibition.
abstract: The authors introduce a real-time model of acoustic prepulse inhibition (PPI) and facilitation (PPF) in animals and humans. The model incorporates excitatory and facilitatory pathways activated by the positive value of changes in noise level in the environment and an inhibitory pathway activated by the absolute value of changes in noise level. Whereas excitation and facilitation are exponential functions, inhibition is a linear function of the input noise expressed in decibels. The model describes many properties of PPI and PPF that include, among others, their dependency on prepulse intensity and duration, duration of the lead interval, and changes in background noise. The model also describes how specific brain lesions enhance the strength of the startle response and impair PPI. Finally, the model correctly predicts how PPI depends on pulse intensity.
authors.affiliation: Department of Psychological and Brain Sciences, Duke University, Durham, NC 27708, USA. nestor@duke.edu
authors.forename: Nestor A
authors.initials: NA
authors.lastname: Schmajuk
authors.forename: José A
authors.initials: JA
authors.lastname: Larrauri
mesh_terms: D000161:Acoustic Stimulation / Q000379:methods; D000818:Animals; D003198:Computer Simulation; D004307:Dose-Response Relationship, Radiation; D006801:Humans; D009433:Neural Inhibition / Q000502:physiology*; D016571:Neural Networks, Computer; D011237:Predictive Value of Tests; D011930:Reaction Time / Q000502:physiology; D013216:Reflex, Startle / Q000502:physiology; D013997:Time Factors