Mechanisms in classical conditioning :
Schmajuk, Nestor A.,
Mechanisms in classical conditioning : a computational approach / Nestor Schmajuk. - Cambridge : Cambridge University Press, 2010. - 1 online resource (xvii, 485 pages) : digital, PDF file(s).
Title from publisher's bibliographic system (viewed on 05 Oct 2015).
pt. I. Introduction. Classical conditioning : data and theories -- pt. II. Attentional and associative mechanisms. An attentional-associative model of conditioning ; Simple and compound conditioning ; The neurobiology of classical conditioning ; Latent inhibition ; The neurobiology of latent inhibition ; Creativity ; Overshadowing and blocking ; Extinction ; The neurobiology of extinction -- pt. III. Configural mechanisms. A configural model of conditioning ; Occasion setting ; The neurobiology of occasion setting -- pt. IV. Attentional, associative, configural, and timing mechanisms. Configuration and timing : timing and occasion setting ; Attention and configuration : extinction cues ; Attention, association and configuration : causal learning and inferential reasoning -- pt. V. Conclusion : mechanisms of classical conditioning.
What mechanisms are involved in enabling us to generate predictions of what will happen in the near future? Although we use associative mechanisms as the basis to predict future events, such as using cues from our surrounding environment, timing, attentional, and configural mechanisms are also needed to improve this function. Timing mechanisms allow us to determine when those events will take place. Attentional mechanisms ensure that we keep track of cues that are present when unexpected events occur and disregard cues present when everything happens according to our expectations. Configural mechanisms make it possible to combine separate cues into one signal that predicts an event different from that predicted individually by separate cues. Written for graduates and researchers in neuroscience, computer science, biomedical engineering and psychology, the author presents neural network models that incorporate these mechanisms and shows, through computer simulations, how they explain the multiple properties of associative learning.
9780511711831 (ebook)
Conditioned response--Computer simulation.
Neural networks (Computer science)
BF319 / .S357 2010
153.1/526
Mechanisms in classical conditioning : a computational approach / Nestor Schmajuk. - Cambridge : Cambridge University Press, 2010. - 1 online resource (xvii, 485 pages) : digital, PDF file(s).
Title from publisher's bibliographic system (viewed on 05 Oct 2015).
pt. I. Introduction. Classical conditioning : data and theories -- pt. II. Attentional and associative mechanisms. An attentional-associative model of conditioning ; Simple and compound conditioning ; The neurobiology of classical conditioning ; Latent inhibition ; The neurobiology of latent inhibition ; Creativity ; Overshadowing and blocking ; Extinction ; The neurobiology of extinction -- pt. III. Configural mechanisms. A configural model of conditioning ; Occasion setting ; The neurobiology of occasion setting -- pt. IV. Attentional, associative, configural, and timing mechanisms. Configuration and timing : timing and occasion setting ; Attention and configuration : extinction cues ; Attention, association and configuration : causal learning and inferential reasoning -- pt. V. Conclusion : mechanisms of classical conditioning.
What mechanisms are involved in enabling us to generate predictions of what will happen in the near future? Although we use associative mechanisms as the basis to predict future events, such as using cues from our surrounding environment, timing, attentional, and configural mechanisms are also needed to improve this function. Timing mechanisms allow us to determine when those events will take place. Attentional mechanisms ensure that we keep track of cues that are present when unexpected events occur and disregard cues present when everything happens according to our expectations. Configural mechanisms make it possible to combine separate cues into one signal that predicts an event different from that predicted individually by separate cues. Written for graduates and researchers in neuroscience, computer science, biomedical engineering and psychology, the author presents neural network models that incorporate these mechanisms and shows, through computer simulations, how they explain the multiple properties of associative learning.
9780511711831 (ebook)
Conditioned response--Computer simulation.
Neural networks (Computer science)
BF319 / .S357 2010
153.1/526