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Computational Models of Hallucinations

  • Renaud Jardri
  • Sophie Denève

Abstract

Recent advances in theoretical neuroscience have provided new insights into information processing within large brain-like networks operating in an uncertain world. The computational framework can overcome some of the complexity within the object of study by predicting how basic changes in neural architecture may lead to systems-level changes that translate into changes in behavior. Computational models offer ways to unify basic neurochemical findings with data from more macroscopic levels and to start to apply these findings to cognitive sciences and psychiatry. Some of these approaches have been used to investigate the underlying mechanisms of subjective experiences, such as hallucinations, which can spontaneously emerge into consciousness in the absence of any corresponding external stimuli. This chapter describes some recent theoretical studies on four categories of positive symptoms of schizophrenia: neurodynamics, noise, disconnectivity, and Bayesian models of hallucinations. Results from simulations of these neural networks as well as the potential alterations leading to aberrant experiences are presented and discussed.

Keywords

Positive Symptom Energy Landscape Stochastic Noise Attractor Network Perceptual Illusion 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Abbreviations

COMT

Catechol-O-methyltransferase

GABA

Gamma amino-butyric acid

GAD-67

67 kDa Isoform of the glutamic acid decarboxylase

IF

Integrate-and-fire neuron

JTC

Jumping-to-conclusion

LBP

Loopy belief propagation

MET158

Methionine at position 158

NMDA

N-Methyl-d-aspartic acid

P(x|y)

Conditional probability of the event x given the occurrence of the event y

RD2

D2 Dopamine receptor

W

Weighting factor

λ

Precision of the prior. This hyperparameter encodes uncertainty and noise in the Expectation-Maximization algorithm

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Copyright information

© Springer Science+Business Media New York 2013

Authors and Affiliations

  1. 1.Functional Neurosciences & Disorders Laboratory, UDSLUniversity Lille North of FranceLilleFrance
  2. 2.Group for Neural Theory, LNC, INSERM U-960, Institute of Cognitive Studies (DEC)École Normale SupérieureParisFrance
  3. 3.Pediatric Psychiatry DepartmentUniversity Medical Centre of Lille (CHU Lille)LilleFrance

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