Cognitive Biases in Health and Psychiatric Disorders: Neurophysiological Foundations

291 Pages·2020·5.473 MB·English

by  Tatjana Aue (editor), Hadas Okon-Singer (editor)

“Don’t believe everything you think.”
Louise Penny, A Great Reckoning
To
Guido, Maximilian, Benjamin, and Anna
Noam, Yaron, and Shachar
Cognitive Biases in Health
and Psychiatric Disorders:
Neurophysiological Foundations
Cognitive Biases
in Health and
Psychiatric Disorders:
Neurophysiological
Foundations
Edited by
Tatjana Aue
Hadas Okon-Singer
Academic Press is an imprint of Elsevier
125 London Wall, London EC2Y 5AS, United Kingdom
525 B Street, Suite 1650, San Diego, CA 92101, United States
50 Hampshire Street, 5th Floor, Cambridge, MA 02139, United States
The Boulevard, Langford Lane, Kidlington, Oxford OX5 1GB, United Kingdom
© 2020 Elsevier Inc. All rights reserved.
No part of this publication may be reproduced or transmitted in any form or by any means,
electronic or mechanical, including photocopying, recording, or any information storage
and retrieval system, without permission in writing from the publisher. Details on how to
seek permission, further information about the Publisher’s permissions policies and our
arrangements with organizations such as the Copyright Clearance Center and the Copyright
Licensing Agency, can be found at our website: www.elsevier.com/permissions.
This book and the individual contributions contained in it are protected under copyright by the
Publisher (other than as may be noted herein).
Notices
Knowledge and best practice in this field are constantly changing. As new research and
experience broaden our understanding, changes in research methods, professional practices, or
medical treatment may become necessary.
Practitioners and researchers must always rely on their own experience and knowledge in
evaluating and using any information, methods, compounds, or experiments described herein.
In using such information or methods they should be mindful of their own safety and the safety
of others, including parties for whom they have a professional responsibility.
To the fullest extent of the law, neither the Publisher nor the authors, contributors, or editors,
assume any liability for any injury and/or damage to persons or property as a matter of products
liability, negligence or otherwise, or from any use or operation of any methods, products,
instructions, or ideas contained in the material herein.
Library of Congress Cataloging-in-Publication Data
A catalog record for this book is available from the Library of Congress
British Library Cataloguing-in-Publication Data
A catalogue record for this book is available from the British Library
ISBN: 978-0-12-816660-4
For information on all Academic Press publications
visit our website at https://www.elsevier.com/books-and-journals
Publisher: Nikki Levy
Acquisitions Editor: Joslyn Chaiprasert-Paguio
Editorial Project Manager: Samantha Allard
Production Project Manager: Surya Narayanan Jayachandran
Cover Designer: Mark Rogers
Typeset by SPi Global, India
Contributors
Numbers in parenthesis indicate the pages on which the authors’ contributions begin.
Elinor Abado (19), Department of Psychology; The Integrated Brain and Behavior
Research Center (IBBR), University of Haifa, Haifa, Israel
Orly Adler (139), Department of Psychology and The Institute of Information Processing
and Decision Making, University of Haifa, Haifa, Israel
Umkalthoom Alzubaidi (1), School of Psychology and Clinical Language Sciences,
Reading, University of Reading, United Kingdom
Tatjana Aue (41), Department of Psychology, University of Bern, Bern, Switzerland
Yasmene Bajandouh (1), School of Psychology and Clinical Language Sciences,
Reading, University of Reading, United Kingdom
Anna Benedict (119), Department of Psychology, University of Notre Dame, Notre
Dame, IN, United States
Matthew Burke (99), University of British Columbia, Vancouver, BC, Canada
Judith K. Daniels  (71), Department of Clinical Psychology and Experimental
Psychopathology, University of Groningen, Groningen, The Netherlands
Nazanin Derakhshan  (261), Department of Psychological Sciences, Birkbeck
University of London, London, United Kingdom
Mihai Dricu (41), Department of Psychology, University of Bern, Bern, Switzerland
Jonas Everaert (193), Department of Experimental-Clinical and Health Psychology,
Ghent University, Ghent, Belgium
J.A. Faunce (173), Department of Psychology, Virginia Polytechnic Institute and State
University, Blacksburg, VA, United States
B.H. Friedman (173), Department of Psychology, Virginia Polytechnic Institute and
State University, Blacksburg, VA, United States
Rivkah Ginat-Frolich (243), Department of Psychology and the Integrated Brain and
Behavior Research Center, University of Haifa, Haifa, Israel
S.S. Grant (173), Department of Psychology, Virginia Polytechnic Institute and State
University, Blacksburg, VA, United States
A.M. Huskey (173), Department of Psychology, Virginia Polytechnic Institute and State
University, Blacksburg, VA, United States
Jingwen Jin (215), Department of Psychology; The State Key Laboratory of Brain and
Cognitive Sciences, The University of Hong Kong, Pok Fu Lam, Hong Kong
xiii
xiv Contributors
Peter J. de Jong  (71), Department of Clinical Psychology and Experimental
Psychopathology, University of Groningen, Groningen, The Netherlands
Ellen Jopling (99), University of British Columbia, Vancouver, BC, Canada
Ernst H.W. Koster (193), Department of Experimental-Clinical and Health Psychology,
Ghent University, Ghent, Belgium
Laura Kress (41), Department of Psychology, University of Bern, Bern, Switzerland;
Department of Psychology, University of Uppsala, Uppsala, Sweden
Joelle LeMoult (99), University of British Columbia, Vancouver, BC, Canada
Aprajita Mohanty (215), Department of Psychology, Stony Brook University, Stony
Brook, NY, United States
Hadas Okon-Singer  (19), Department of Psychology; The Integrated Brain and
Behavior Research Center (IBBR), University of Haifa, Haifa, Israel
Ainat Pansky (139), Department of Psychology and The Institute of Information
Processing and Decision Making, University of Haifa, Haifa, Israel
Thalia Richter (19), Department of Psychology; The Integrated Brain and Behavior
Research Center (IBBR), University of Haifa, Haifa, Israel
Victoria Shaffer (119), Department of Psychology, University of Notre Dame, Notre
Dame, IN, United States
Tomer Shechner (243), Department of Psychology and the Integrated Brain and
Behavior Research Center, University of Haifa, Haifa, Israel
Tamara J. Sussman (215), Department of Psychiatry, Columbia University Irving
Medical Center; Department of Psychiatry, New York State Psychiatric Institute,
New York, NY, United States
Alison Tracy (99), University of British Columbia, Vancouver, BC, Canada
Julia Vogt (1), School of Psychology and Clinical Language Sciences, Reading,
University of Reading, United Kingdom
Jessica Wilson (99), University of British Columbia, Vancouver, BC, Canada
K. Lira Yoon (119), Department of Psychology, University of Notre Dame, Notre Dame,
IN, United States
Preface
Biases in information processing have attracted major research interest in
examining psychiatric disorders such as anxiety and depression, as well as
in studying populations at risk of developing psychopathology. Even among
healthy individuals, these biases have been receiving increasing attention. This
is b ecause our feelings about our own lives and about other people are strongly
influenced by how we attend to our environment, what we expect, and how
we interpret or memorize a given situation. Cognitive Biases in Health and
Psychiatric Disorders: Neurophysiological Foundations offers a comprehen-
sive and in-depth description of these critical biases, provides examples from
relevant cutting-edge research, and discusses methodological developments,
implications, future directions, and open questions.
The traditional view is that biased information processing is categorically
unhealthy and disadvantageous. This book reveals evidence contradicting this
outdated view by delineating adaptive and maladaptive forms of positive and
negative biases. Such evidence shows that no bias is “bad” or “good” per se.
Rather, often the strength of a bias is what determines its degree of adaptability.
Identifying and applying the correct dose of a given bias may therefore be cru-
cial to leading a healthy and satisfactory life.
The fact that biases can interact (e.g., reinforce each other) has also been
disregarded until lately. This omission may play a major role in the difficul-
ties in accessing and distinguishing between different mental states or psychi-
atric diagnoses (e.g., anxiety vs depression) and in assessing the origins of such
states. Indeed, understanding the mechanisms underlying mental disorders (or
well-being in general) may not always be as simple as has often been proposed
in the literature. Consideration of causal influences between biases can create a
picture of human functioning that is not only more complex and mentally chal-
lenging but also more realistic. A better understanding of any given phenom-
enon usually goes along with its facilitated convertibility. Hence, in the long
run, interrelated investigations have the potential to foster quality of life more
rapidly and more effectively.
The chapters of this book provide a comprehensive summary of studies
examining biases in attention, expectancy, interpretation, and memory. Each
chapter features information regarding leading theoretical views, experimental
paradigms for studying the specific bias, and behavioral, neural, and somato-
visceral findings. Moreover, in each chapter, the authors refer to limitations
in existing literature and suggest future research directions to achieve a better
understanding of each bias. Finally, individual chapters are dedicated to devel-
opmental aspects of processing biases, causal relations between the different bi-
ases, and implications of the scientific and theoretical research for everyday life.
xv
xvi Preface
To date, most research on processing biases has focused on attention bi-
ases. In Chapter 1, Vogt, Bajandouh, and Alzubaidi (2020) underscore the
importance of attention biases to positive stimuli. Biased attention to positive-
rewarding cues is thought to be based on their relevance, which originates in
their evolutionary significance, in the positive valence they acquired via learn-
ing processes, or in their relevance to current goals. Attention biases to positive
stimuli are associated with neural activation in regions related to reward, at-
tention, and control, including the amygdala, the anterior cingulate cortex, and
the dorsolateral prefrontal cortex. Autonomic measures are rather inconsistent,
although changes in facial muscle activity, heart rate, and skin conductance
have been associated with attention biases to positive stimuli. Attention biases
toward positive stimuli have been commonly considered an attribute of healthy
behavior, with clinical and subclinical populations showing decreased strength
of such biases. Yet, in certain situations, these biases can be problematic, as
in the case of orienting attention toward high caloric tasty food among obese
participants.
In Chapter 2, Abado, Richter, and Okon-Singer (2020) focus on biased at-
tention toward negative stimuli (here, threat cues), which includes facilitated
engagement of attention to threat, followed by difficulty in disengaging atten-
tion from the threat cue and subsequently by enhanced attentional avoidance.
These three attention bias components have been studied extensively using vari-
ous methods, paradigms, stimuli, and populations. Corresponding studies point
to consistent biases among participants with anxiety disorders, while evidence
regarding attention bias among participants with depression is mixed. Biases in
such clinical populations are accompanied by abnormal neural activation in the
amygdala, the thalamic pulvinar nucleus, and prefrontal and parietal regions, as
well as abnormal autonomic reactivity that includes eye movements, heart rate,
blood pressure, and skin conductance. Attention biases also appear in individu-
als with subclinical levels of anxiety, although disengagement and avoidance
are less robust in subclinical populations, possibly due to large interindividual
differences.
In Chapter 3, Dricu, Kress, and Aue (2020) focus on positive expectancy
biases, and specifically on optimism bias. Optimism bias (also termed overop-
timism) refers to an individual’s tendency to estimate positive events as more
likely and negative events as less likely than what would be predicted by a ra-
tional consideration of the information at hand. This type of responding is hard
to overcome and may even stabilize over time, as demonstrated by the fact that
information in the environment supporting an initial optimism bias is more eas-
ily integrated than information that challenges overoptimistic expectancies. It is
worth noting that overoptimism not only does exist for the self (i.e., personal op-
timism bias) but extends to others with whom we identify (social optimism bias).
Moreover, the bias reverses into a pessimism bias toward unpopular out-groups.
Whether or not optimism bias can be reliably revealed depends on its specific
definition and the paradigm used for its investigation. Among the brain regions