Connectionist models and their properties

Much of the progress in the fields constituting cognitive science has been based upon the use of explicit information processing models, almost exclusively patterned after conventional serial computers. An extension of these ideas to massively parallel, connectionist models appears to offer a number of advantages. After a preliminary discussion, this paper introduces a general connectionist model and considers how it might be used in cognitive science. Among the issues addressed are: stability and noise-sensitivity, distributed decision-making, time and sequence problems, and the representation of complex concepts.     

Loneliness and Suicidal Ideation in Drug‐Using College Students

The college years are marked by social changes and behavioral experimentation which may increase risk of suicidal ideation. We propose a novel pathway for the development of suicidal thoughts between two established suicide risk factors, loneliness and drug use, which have not been examined in a nonclinical sample. Data were collected from 207 undergraduate drug‐using students at a large southeastern university. As hypothesized, suicidal ideation was positively correlated with both loneliness (r = .40) and drug use (r = .29). After controlling for several demographic variables, social desirability, and anxiety sensitivity, drug use was tested as a potential mediator in the loneliness–suicidal ideation link using a single‐mediator model. Results indicated a significant indirect (mediated) effect of loneliness on suicidal ideation via drug use (ab = 0.09, 95% CI: 0.02–0.18), suggesting that loneliness may contribute to suicidal ideation through increased drug use among college students. Identification of and intervention with students reporting loneliness and drug use may be a promising suicide prevention strategy on college campuses.