<?xml version="1.0" encoding="UTF-8"?>
<record
    xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"
    xsi:schemaLocation="http://www.loc.gov/MARC21/slim http://www.loc.gov/standards/marcxml/schema/MARC21slim.xsd"
    xmlns="http://www.loc.gov/MARC21/slim">

  <leader>04981nam a22001577a 4500</leader>
  <datafield tag="999" ind1=" " ind2=" ">
    <subfield code="c">19465</subfield>
    <subfield code="d">19465</subfield>
  </datafield>
  <datafield tag="020" ind1=" " ind2=" ">
    <subfield code="a">9780443155482</subfield>
  </datafield>
  <datafield tag="082" ind1=" " ind2=" ">
    <subfield code="a">612.85 EGG</subfield>
  </datafield>
  <datafield tag="100" ind1=" " ind2=" ">
    <subfield code="a">Eggermont, Jos J.</subfield>
  </datafield>
  <datafield tag="245" ind1=" " ind2=" ">
    <subfield code="a">Brain responses to auditory mismatch and novelty detection : predictive coding from cocktail parties to auditory-related disorders /</subfield>
    <subfield code="c">Jos J Eggermont</subfield>
  </datafield>
  <datafield tag="260" ind1=" " ind2=" ">
    <subfield code="a">London :</subfield>
    <subfield code="b">Academic Press,</subfield>
    <subfield code="c">2023.</subfield>
  </datafield>
  <datafield tag="300" ind1=" " ind2=" ">
    <subfield code="a">458 p.</subfield>
  </datafield>
  <datafield tag="505" ind1=" " ind2=" ">
    <subfield code="a">Cover
Title page
Table of Contents
Copyright
Preface
Reference
Abbreviations
Chapter 1: A primer on predictive coding and network modeling
Abstract
1.1: Introduction
1.2: Hierarchical learning
1.3: From hierarchical learning to predictive coding
1.4: Predictive coding and Bayesian inference
1.5: Brain areas and activity involved in predictive coding
1.6: Modeling networks underlying predictive coding
1.7: Predictive coding networks and cognition
1.8: Is predictive coding complete?
1.9: Summary
References
Chapter 2: Setting the stage: Cocktail parties, auditory streaming, mismatch negativity, and stimulus-specific adaptation
Abstract
2.1: Introduction
2.2: Auditory stream segregation
2.3: Human electrophysiology and neural imaging
2.4: Stimulus-specific adaptation in animal models as an equivalent of the MMN
2.5: Novelty detection
2.6: Mismatch responses and predictive coding
2.7: Summary
References
Chapter 3: Neural adaptation and forward masking along the auditory pathway
Abstract
3.1: Introduction
3.2: Electrophysiology of adaptation and forward masking
3.3: A putative role of neural adaptation in explaining the mismatch negativity
3.4: Summary
References
Chapter 4: Animal studies of deviance detection along the auditory pathway
Abstract
4.1: MMN in animals?
4.2: Stimulus-specific adaptation in animals
4.3: The role of auditory cortex in mismatch detection and predictive coding
4.4: Summary
References
Chapter 5: Auditory cortical event-related potentials in the human brain
Abstract
5.1: Introduction
5.2: Effects of adaptation, attention, and memory
5.3: Deviance detection
5.4: Novelty processing
5.5: Summary
References
Chapter 6: Development and maturation aspects of predictive coding
Abstract
6.1: Introduction
6.2: Maturation of subcortical activity
6.3: Cortical auditory evoked potentials
6.4: Maturation of the mismatch response
6.5: Novelty detection. Maturation of the P300 complex
6.6: Summary
References
Chapter 7: Role of event-related potentials and brain rhythms in predictive coding
Abstract
7.1: Auditory stream segregation
7.2: Networks underlying error responses in predictive coding
7.3: The role of auditory areas in predictive coding
7.4: Are brain oscillations a substitute for ERPs in predictive coding?
7.5: Local vs global deviance
7.6: Summary
References
Chapter 8: Predictive coding in autism spectrum disorder, attention-deficit/hyperactivity disorder, and dyslexia
Abstract
8.1: Introduction
8.2: Characterizing auditory aspects of ADHD and ASD
8.3: Changes in auditory brainstem responses and cortical auditory evoked potentials
8.4: Changes in MMN and the P3 complex
8.5: Do ERPs diagnose between ASD and ADHD?
8.6: Does predictive coding contribute?
8.7: Developmental dyslexia
8.8: Summary
References
Chapter 9: Predictive coding in aging, tinnitus, MCI, and Alzheimer&#x2019;s disease
Abstract
9.1: Auditory aspects of aging
9.2: Tinnitus
9.3: ERPs in aging, mild cognitive impairment, and Alzheimer's disease
9.4: Summary
References
Chapter 10: Brain networks involved in deviance and novelty detection: Are they sensory modality specific?
Abstract
10.1: Introduction
10.2: Sensory modality-dependent mismatch negativity
10.3: Network changes underlying cognition
10.4: Networks underlying prediction-error coding
10.5: Summary
References
Chapter 11: Predictive coding in music, speech, and language
Abstract
11.1: Right-hemisphere dominance
11.2: Similar brain areas are activated by music and language
11.3: Cortical pathways in linguistic processing
11.4: Role of brain rhythms in music and language coding
11.5: Predictive coding in more detail
11.6: Alternative models to predictive coding in speech and language
11.7: Summary
References
Chapter 12: Network changes underlying neural disorders: Relation to the MMN networks
Abstract
12.1: Network changes in tinnitus
12.2: Functional connectivity in dyslexia
12.3: Network changes across aging and neurodegenerative disorders
12.4: Autism spectrum disorder
12.5: ADHD
12.6: MCI and Alzheimer's disease
12.7: Integration of the MMN network and disorder-specific changes
12.8: Summary
References
Appendix: A primer on cortical auditory evoked potentials and magnetic fields
A.1: Obligatory&#x2014;Exogenous&#x2014;Cortical auditory evoked potentials
A.2: Description of CAEP components
A.3: Endogenous auditory event-related potentials
References
Index</subfield>
  </datafield>
  <datafield tag="650" ind1=" " ind2=" ">
    <subfield code="a">Brain</subfield>
  </datafield>
  <datafield tag="650" ind1=" " ind2=" ">
    <subfield code="a">Hearing disorders</subfield>
  </datafield>
  <datafield tag="650" ind1=" " ind2=" ">
    <subfield code="a">human auditory evoked potentials</subfield>
  </datafield>
  <datafield tag="952" ind1=" " ind2=" ">
    <subfield code="0">0</subfield>
    <subfield code="1">0</subfield>
    <subfield code="4">0</subfield>
    <subfield code="7">0</subfield>
    <subfield code="8">R-27/1</subfield>
    <subfield code="a">AIISH</subfield>
    <subfield code="b">AIISH</subfield>
    <subfield code="d">2024-07-09</subfield>
    <subfield code="l">0</subfield>
    <subfield code="o">612.85 EGG</subfield>
    <subfield code="p">23477</subfield>
    <subfield code="r">2024-07-09 00:00:00</subfield>
    <subfield code="w">2024-07-09</subfield>
    <subfield code="y">RFT</subfield>
  </datafield>
  <datafield tag="952" ind1=" " ind2=" ">
    <subfield code="0">0</subfield>
    <subfield code="1">0</subfield>
    <subfield code="4">0</subfield>
    <subfield code="7">0</subfield>
    <subfield code="8">50/1</subfield>
    <subfield code="a">AIISH</subfield>
    <subfield code="b">AIISH</subfield>
    <subfield code="d">2024-07-09</subfield>
    <subfield code="l">0</subfield>
    <subfield code="o">612.85 EGG;1</subfield>
    <subfield code="p">23478</subfield>
    <subfield code="r">2024-07-09 00:00:00</subfield>
    <subfield code="w">2024-07-09</subfield>
    <subfield code="y">STS</subfield>
  </datafield>
</record>
