Switch to: Citations

Add references

You must login to add references.
  1. Addiction: Decreased reward sensitivity and increased expectation sensitivity conspire to overwhelm the brain's control circuit.Nora D. Volkow, Gene-Jack Wang, Joanna S. Fowler, Dardo Tomasi, Frank Telang & Ruben Baler - 2010 - Bioessays 32 (9):748-755.
    Based on brain imaging findings, we present a model according to which addiction emerges as an imbalance in the information processing and integration among various brain circuits and functions. The dysfunctions reflect (a) decreased sensitivity of reward circuits, (b) enhanced sensitivity of memory circuits to conditioned expectations to drugs and drug cues, stress reactivity, and (c) negative mood, and a weakened control circuit. Although initial experimentation with a drug of abuse is largely a voluntary behavior, continued drug use can eventually (...)
    Direct download (5 more)  
     
    Export citation  
     
    Bookmark   11 citations  
  • Conflict monitoring and anterior cingulate cortex: an update.Matthew M. Botvinick, Jonathan D. Cohen & Cameron S. Carter - 2004 - Trends in Cognitive Sciences 8 (12):539-546.
    One hypothesis concerning the human dorsal anterior cingulate cortex (ACC) is that it functions, in part, to signal the occurrence of conflicts in information processing, thereby triggering compensatory adjustments in cognitive control. Since this idea was first proposed, a great deal of relevant empirical evidence has accrued. This evidence has largely corroborated the conflict-monitoring hypothesis, and some very recent work has provided striking new support for the theory. At the same time, other findings have posed specific challenges, especially concerning the (...)
    Direct download (6 more)  
     
    Export citation  
     
    Bookmark   155 citations  
  • The Nature of Statistical Learning Theory.Vladimir Vapnik - 2000 - Springer: New York.
    The aim of this book is to discuss the fundamental ideas which lie behind the statistical theory of learning and generalization. It considers learning as a general problem of function estimation based on empirical data. Omitting proofs and technical details, the author concentrates on discussing the main results of learning theory and their connections to fundamental problems in statistics. This second edition contains three new chapters devoted to further development of the learning theory and SVM techniques. Written in a readable (...)
    Direct download  
     
    Export citation  
     
    Bookmark   66 citations