Reasoning: The Neuroscience of How We Think

By Daniel Krawczyk

Reasoning: The Neuroscience of How We Think is a comprehensive guide to the core topics related to a thorough understanding of reasoning. It presents the current knowledge of the subject in a unified, complete manner, ranging from animal studies, to applied situations, and is the only book available that presents a sustained focus on the neurobiological processes behind reasoning throughout all chapters, while also synthesizing research from animal behavior, cognitive psychology, development, and philosophy for a truly multidisciplinary approach. The book considers historical perspectives, state-of-the-art research methods, and future directions in emerging technology and cognitive enhancement.

Written by an expert in the field, this book provides a coherent and structured narrative appropriate for students in need of an introduction to the topic of reasoning as well as researchers seeking well-rounded foundational content. It is essential reading for neuroscientists, cognitive scientists, neuropsychologists and others interested in the neural mechanisms behind thinking, reasoning and higher cognition.

• Provides a comparative perspective considering animal cognition and its relevance to human reasoning
• Includes developmental and lifespan considerations throughout the book
• Discusses technological development and its role in reasoning, both currently and in the future
• Considers perspectives from not only neuroscience, but cognitive psychology, philosophy, development, and animal behavior for a multidisciplinary treatment
• Contains highlight boxes featuring additional details on methods, historical descriptions and experimental tasks

• Language: English
• Publisher: Academic Press
• Release date: Nov 13, 2017
• ISBN: 9780128095768

Daniel Krawczyk

Dan Krawczyk is an Associate Professor & Deputy Director of the Center for BrainHealth®, and the Francis Chair in Behavioral and Brain Sciences. Dr. Krawczyk is also an Associate Professor in Psychiatry at the University of Texas Southwestern Medical Center. His extensive multi-disciplinary research has investigated the neural basis of reasoning in veterans, healthy adults, adolescents, and individuals with disorders including dementia, brain injury, and autism spectrum disorders. His Department of Defense-funded research with U.S. military veterans has helped to provide a greater understanding of how reasoning strategies can enhance rehabilitation of brain functions after traumatic brain injury. He has also received support from the Defense Advanced Research Projects Agency (DARPA) to evaluate social reasoning skills across cultures. Dr. Krawczyk holds a Ph.D. from the University of California, Los Angeles and was previously a Ruth L. Kirschstein postdoctoral fellow at the University of California, Berkeley. He has appeared on television, radio, & frequently in print media. He recently spoke at a TEDx talk https://youtu.be/J3ktgPQbUvo & Perot Museum of Science, Dallas, TX. https://youtu.be/wcgS77KlUPE. For more up to date information on Dr. Krawczyk visit https://www.danielkrawczyk.org/

Book preview

Reasoning

The Neuroscience of How We Think

Daniel C. Krawczyk

The University of Texas at Dallas, Richardson, TX, United States

University of Texas Southwestern Medical Center, Dallas, TX, United States

Table of Contents

Cover image

Title page

Copyright

Foreword

Acknowledgments

Chapter 1. Introduction to Reasoning

Introduction to Reasoning

Defining Reasoning

How We Study Reasoning

Categorizing Reasoning

Putting it All Together

Summary

End-of-Chapter Thought Questions

Chapter 2. The History of Reasoning Research

History of Reasoning

Early Approaches to Studying Reasoning

Early Psychology of Reasoning

Cognitive Psychology of Reasoning

The Evolution of Cognitive Modeling

Developmental Psychology of Reasoning

Neuroscience of Reasoning

Summary

End-of-Chapter Thought Questions

Chapter 3. The Neuroscience of Reasoning

The Neuroscience of Reasoning

Anatomical Considerations

Neuroscience of Relational Reasoning

Functional Neuroanatomy of Knowledge

Deduction, Induction, and the Brain

Neural Networks of Reasoning

Summary

End-of-Chapter Thought Questions

Chapter 4. Comparative Reasoning: A Cross-Species Perspective

Biological Differences Between Animals and Humans

Comparative Biology

Associative Learning as a Basis for Animal Reasoning

Association as a Basis for Problem Solving

Causal Reasoning in Nonhumans

Social Cognition

Relational Reasoning in Animals

Summary

End-of-Chapter Thought Questions

Chapter 5. Reasoning Origins: Human Development During Childhood

Reasoning Origins

Assessing Cognitive Abilities

Development of Reasoning in Childhood

Causal Reasoning in Children

Deduction and Induction in Children

Relational Reasoning in Children

Judgment and Decision Making in Children

Development of Moral Reasoning

Summary

End-of-Chapter Thought Questions

Chapter 6. Reasoning Over the Lifespan

Reasoning Across the Lifespan

Biological Changes in Adolescence

The Brain and Reasoning From Adolescence to Adulthood

Cognition and Behavior in Adolescents

Executive Control and Advanced Reasoning Skills

Brain Changes Associated With Aging Adults

Changes in Cognition With Aging

Practical Reasoning in the Older Years

Summary

End-of-Chapter Questions

Chapter 7. Disorders of Reasoning

Reasoning Disorders

Cognitive Factors in Reasoning Disorders

Social Deficits and Reasoning

Neurology of Reasoning Deficits

Disorders of Relational Reasoning

Disorders of Decision Making

Disruptions of Moral Reasoning

Summary

End-of-Chapter Thought Questions

Chapter 8. Reasoning About Contingencies, Correlations, and Causes

Reasoning About Contingencies, Correlations, and Causes

Establishing Cause as a Building Block for Knowledge

Correlation or Causation?

The Challenges of Establishing Cause

Illusions of Control

Perceiving Causal Influence

Summary

End of Chapter Thought Questions

Chapter 9. Deduction and Induction

Deductive and Inductive Reasoning

Defining Deduction

Deductive Reasoning in the Laboratory

Deductive Reasoning in Everyday Life

Inductive Reasoning

Inductive Reasoning in the Laboratory

Factors That Affect Inductive Reasoning

Summary

End-of-Chapter Thought Questions

Chapter 10. Analogical Reasoning

Reasoning by Analogy

Relational Correspondences: The Building Blocks of Analogies

Evaluating Similarity

Placing Items Into Correspondence

System Mappings

Semantic Memory and the Role of Associations

Analogical Reminding

Analogical Reasoning in Everyday Life and the Laboratory

Summary

End-of-Chapter Thought Questions

Chapter 11. Decision Making and Abductive Reasoning

How Do We Decide?

The Science of Decision Making

Simple and Complex Decisions

Rational Models

Biases and Heuristics

Abductive Reasoning

Decision Making and the Brain

Summary

End-of-Chapter Thought Questions

Chapter 12. Social Cognition: Reasoning With Others

Social Cognition: Reasoning With Others

Reasoning About the Minds of Others

Social Reasoning in Other Species

Social Ability and Face Perception

Social Aspects of Reasoning

Social Aspects of Decision Making

The Neurosceince of Trust

The Effects of Culture on Social Reasoning

Summary

End-of-Chapter Thought Questions

Chapter 13. Future Directions in Reasoning: Emerging Technology and Cognitive Enhancement

Future Directions in Reasoning

Advances in Automated Computing

Artificial Intelligence and Human Reasoning

Future Directions

Summary

End-of-Chapter Thought Questions

Index

Copyright

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The following was written by a U.S. Government employee within the scope of her official duties and, as such, shall remain in the public domain: Foreword. Therefore, copyright on her work may not be established in the United States (17 U.S.C. § 105). The views expressed in this book are those of the authors and do not necessarily represent those of the National Institutes of Health, the Eunice Kennedy Shriver National Institute of Child Development and Human Development (NICHD), or the U.S. Department of Health and Human Services (DHHS).

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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.

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A catalogue record for this book is available from the British Library

ISBN: 978-0-12-809285-9

For information on all Academic Press publications visit our website at https://www.elsevier.com/books-and-journals

Publisher: Nikki Levy

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Editorial Project Manager: Timothy Bennett

Production Project Manager: Stalin Viswanathan

Cover Designer: Miles Hitchen

Typeset by TNQ Books and Journals

Cover image courtesy of Dominic Krawczyk

Foreword

Across the millennia, many great thinkers have addressed the topic of reasoning and its importance to the human existence (see Chapter 2). But human reasoning likely began long before any written record. For example, early evidence of reasoning at work is found in the toolmaking of pre-Homo sapiens transitional humans Lomekwi 3 hominins’ knapping dated to 3.3 Ma in West Turkana, Kenya (Lewis & Harmand, 2016). And if these prehuman beings possessed reasoning capacities, are there other species with similar abilities (see Chapter 4)? Understanding the origins of reasoning tells us much about the depth and breadth of reasoning.

Elucidating the likely constituent necessary and sufficient cognitive factors that contribute to reasoning (see Chapters 1, 3, and 5) such as memory (especially working and long-term memory), attention, sensory and speeded processing, executive functions, symbolic processing, or fluid intelligence, has taught us that reasoning abilities are not entirely a fixed trait (Plomin & Spinath, 2002), but rather a cognitive state that enables decision making (see Chapters 6 and 11) and successfully and flexibly adapts to a complex and changing environment (Bolger, Mackey, Wang, & Grigorenko, 2014; Mackey, Hill, Stone, & Bunge, 2011). It is fair to state that there is hardly an area of the brain that doesn’t contribute to some type/form of reasoning, further reinforcing the notion that reasoning is a convergence of genetic factors melded to learning and experience to form as unique a brain as the individual reasoning with it.

By studying the life-course development of reasoning (Chapters 5 and 6), as well as the biological bases of reasoning (Chapters 3 and 7), we begin to grasp opportunities to improve reasoning skills (Bergman Nutley et al., 2011; Mackey et al., 2011). Understanding the behavioral characteristics and cognitive foundations of the various types of reasoning (Chapters 8–12) provides new insight into the potential shared and unique inflection points for the engagement of scaffolding, intervention, or educational strategies (Jaeggi, Buschkuehl, Jonides, & Shah, 2011; Mackey et al., 2011).

The advancement of new technologies, especially in computational domains such as widely available robust computing and information processing, mobile computing and social media, context-aware systems, artificial intelligence, computational modeling, and virtual and augmented reality formats, have changed both the nature and the quantity of information reasoned about while also often taxing human reasoning with the quantity and complexity of these data (see Chapter 13). At the same time, computational technologies increasingly assist human reasoning in everyday activities such as the fastest path to drive to work, which store offers the best bargain on the product that most suits your needs and preferences, or using crowd-sourced reviews to inform which is the best Thai restaurant in the area.

Although decades of research have produced great strides in the understanding of the cognitive and neurobiological bases of reasoning in healthy persons, many gaps remain. Far less is known about the typical and atypical human development of this ability and the biological (e.g., genetic and neurobiological) underpinnings of this developmental process. With the emergence of an information society, strong STEM (science/technology/engineering/math) reasoning abilities have become essential for a healthy population and the economic success of the society. Understanding how these reasoning skills develop, identifying developmental challenges and sensitive periods, recognizing risk factors to normal and optimal development, and identifying key prevention and remedial interventions have emerged as critical priorities in the study of developmental cognition and learning.

To move this goal forward, a multidisciplinary working group of leading scientists were brought together as the NICHD Reasoning Work Group during the Winter 2014–2015 to identify current knowledge and advancement gaps. Speakers focused on issues that could be addressed in both the short term, as well as those requiring significantly more time and/or preliminary data before the field could fully address the issues. The overall goal was to move the field toward a better understanding of the development of reasoning ability with the hope to improve the health and health decision making, the welfare, and the STEM success of Americans, when possible, by improving teaching/learning of domains, such as science and mathematics, that are highly dependent on reasoning abilities, and provide effective remediation for individuals with suboptimal reasoning abilities.

Following these sessions, I had the great pleasure to organize the 2015 Cognitive Neuroscience Annual Conference Mini-Symposium Reasoning: Origins and Development (March 29, 2015), where selected members of the NICHD Reasoning Work Group were invited to present their work and disseminate the Reasoning Work Group’s conclusions, as well as to stimulate research interests in identified gap areas.

The following book is the culmination of that groundwork laid by the NICHD Reasoning Work Group and the extraordinary efforts of one of its members, Dr. Daniel Krawczyk, to reach far beyond the Reasoning Work Group’s discussions and provide a vehicle to more broadly disseminate our current understanding of reasoning in its many instantiations and to provide the next generation of reasoning researchers a firm base and rich understanding of their science, it’s impacts, and gap opportunities. This work is the first of its kind to present an extremely broad swath of the science of reasoning in a comprehensive and easily comprehensible fashion that peaks the interests of the reader with every turn of a page. Whether student or scholar, this volume is certain to become an indispensable tome. It is of course also among the few extant tools to engage junior scientists and open before them an enticing field ready and awaiting their exploration.

It is an honor to be asked to write this Foreword, to introduce you, the reader, to the reasoning puzzles I have come to love and explore, and to welcome all readers to the science than enables our reasoning to solve these puzzles. I hope you will join me in this increasingly critical research.

This is also my opportunity to thank Daniel for taking up the challenge I posed to the NICHD Reasoning Work Group back in 2014 to write a significant volume to cohere what is currently known about reasoning and where are the gaps, and to use a writing style appreciated by the student, the investigator, as well as the interested casual learner. The writing of this book has been a monumental effort; I will never be able to thank him enough. I believe he has succeeded splendidly.

Kathleen Mann Koepke, PhD,     Director, Math & Science Cognition, Reasoning, & Learning - Development & Disorders Program

Eunice Kennedy Shriver,     National Institute of Child Health & Human Development (NICHD), National Institutes of Health (NIH), Bethesda, Maryland USA

June 2, 2017

References

Bergman Nutley S, Söderqvist S, Bryde S, Thorell L.B, Humphreys K, Klingberg T. Gains in fluid intelligence after training non-verbal reasoning in 4-year-old children: A controlled, randomized study. Developmental Science. 2011;14(3):591–601. doi: 10.1111/j.1467-7687.2010.01022.x.

Bolger D.J, Mackey A.P, Wang M, Grigorenko E.L. The role and sources of individual differences in critical-analytic thinking: A capsule overview. Educational Psychology Review. 2014;26(4):495–518. doi: 10.1007/s10648-014-9279-x.

Jaeggi S.M, Buschkuehl M, Jonides J, Shah P. Short- and long-term benefits of cognitive training. Proceedings of the National Academy of Sciences of the United States of America. 2011;108(25):10081–10086. doi: 10.1073/pnas.1103228108.

Lewis J.E, Harmand S. An earlier origin for stone tool making: Implications for cognitive evolution and the transition to homo. Philosophical Transactions of the Royal Society B: Biological Sciences. 2016;371(1698) doi: 10.1098/rstb.2015.0233.

Mackey A.P, Hill S.S, Stone S.I, Bunge S.A. Differential effects of reasoning and speed training in children. Developmental Science. 2011;14(3):582–590. doi: 10.1111/j.1467-7687.2010.01005.x.

Plomin R, Spinath F.M. Genetics and general cognitive ability (g). Trends in Cognitive Sciences. 2002;6(4):169–176. http://dx.doi.org/10.1016/S1364-6613(00)01853-2.

Acknowledgments

This project was initiated in part by my participation in a Eunice Kennedy Shriver National Institute of Child Health & Human Development Reasoning Work Group that was convened by Kathy Mann Koepke in 2014. The group consisted of scholars representing a diversity of perspectives on reasoning (Renee Baillargeon, Aaron Blaisdell, Silvia Bunge, Kevin Dunbar, Lisa Freund, Susan Jaeggi, Frank Keil, Ben Rottman, and Fei Xu). Their presentations were most enlightening and helped to set the stage for this book. Special thanks go to Kathy Mann Koepke who was most helpful and supportive throughout the writing process and to Aaron Blaisdell for his contributions to Chapter 4 on reasoning in other species. I thank Jonathan Fugelsang, Michael Vendetti, and two anonymous reviewers for their insights on the organization of the book. My colleagues John Hart, Francesca Filbey, Sandi Chapman, and Bart Rypma helped to motivate this project and inspire the writing.

Many of my colleagues with whom I have studied reasoning and discussed the topic have helped to shape the book content. For this I thank Keith Holyoak, Mark D’Esposito, Barbara Knowlton, John Hummel, Dan Simon, Nancy Gee, Bob Morrison, Lindsey Richland, Dan Levine, Michelle McClelland, Gloria Yang, Ehsan Shokri-Kojori, Kevin Murch, Don Kretz, Amy Boggan, Leanne Young, Adam Teed, Tiffani Jantz Fox, Barry Rodgers, Jameson Miller, Jelena Rakic, Guido Schauer, Kihwan Han, Zhengsi Chang, Mandy Maguire, and Jim Stallings.

Teaching a course on reasoning has afforded me excellent feedback on the topics covered in this book. I especially thank Daniel Mark, David Martinez, Linda Nguyen, Matt Kmiecik, and Michael Lundie for their valuable suggestions. I thank Jim Bartlett and Bob Stillman for being supportive of the project. I also thank Ed Krawczyk, Liz Krawczyk, Lee Drew, George Baxter, Galen Westmoore, John Sterling, Craig Caravaglio, Adam Green, and Bret Grasse for the encouragement, support, and the interesting discussions we have had about the many facets of reasoning.

I thank the staff at Elsevier who have helped to move this project forward and see it to completion. They include April Farr, Joslyn Paguio, Timothy Bennett, and Stalin Viswanathan. I thank Kristine Miranda at the Center for BrainHealth for her critical contributions to the figures, captions, and editing, along with her organization skills and persistence. I thank Dominic Krawczyk for his inspiring cover artwork.

This book is dedicated to my wife Linda Drew who made exceptional contributions to this project from start to finish and to Joshua and Dominic who frequently inspire me to think about a wide range of topics in human reasoning.

Chapter 1

Introduction to Reasoning

Abstract

Reasoning is a complex and multidisciplinary area of study. This book presents a series of overviews of an array of topics in the field. The book proceeds in a bottom-up manner by first introducing research on the brain and reasoning and working up toward social aspects of reasoning and the impacts of technology. Along the way we will cover many categories of reasoning and consider the implications of the nervous system, development, aging, and brain injury on reasoning. Reasoning involves some core features. Three important aspects of reasoning were discussed in this chapter. First, reasoning involves moving from multiple inputs to a single output, which can be a conclusion or an action. Second, reasoning involves multiple steps through a state space to achieve a final outcome. There are numerous ways through the process to achieve different outputs. Third, reasoning involves a mixture of previous knowledge and novel information. The precise combination of these types of information will vary based on the type of problem. The research community must take a broad view and incorporate many research methods to understand the process. It is also important that researchers propose clear operational definitions of the reasoning type that they are planning to study.

Keywords

Cognition; Development; Induction; Neuroscience deduction; Philosophy; Psychology; Reasoning

Outline

Introduction to Reasoning

About This Book

Features of the Book

Defining Reasoning

What Counts as Reasoning?

Factors That Influence Reasoning

How We Study Reasoning

Historical Considerations

A Multidisciplinary Approach

Categorizing Reasoning

Defining Diverse Modes of Thinking

Determining Cause and Effect

Reasoning About Rules

Inductive Inferences

Reasoning and Decision Making

Putting It All Together

Reasoning in Society

What Does the Future Hold?

Summary

End-of-Chapter Thought Questions

References

Key Themes

• The study of reasoning is a multidisciplinary area involving researchers in neuroscience, psychology, economics, computer science, philosophy, and business.

• Reasoning involves moving from multiple inputs to a single output, which can be a conclusion or an action.

• Reasoning involves multiple steps through a state space to achieve a final outcome. There are numerous ways through the process to achieve different conclusions.

• Reasoning involves a mixture of previous knowledge and novel information.

• Reasoning capability is determined by our cognitive operations. It depends upon attention, working memory, and long-term memory.

• Reasoning is determined by the capabilities of an organism’s nervous system. Species with complex brains tend to show greater levels of complexity in reasoning and behavior.

• There are several different categories of reasoning, and these are defined by the complexity of the inputs, the particular operations that occur, and the types of conclusions that can be reached.

• Technological advances have opened up a variety of exciting new avenues in reasoning research including augmenting human reasoning.

Introduction to Reasoning

About This Book

The field of reasoning has a long and diverse history. There was a time when scholars believed that the mind and body were largely separate and that the functions of the mind were somehow unique, possibly defying the laws of nature. This led thinkers to use their own imaginations in order to create theories about how we reason. They did this using those powers of reasoning to construct theories and myths about the operations of the world around them. Over time people began to notice links between the natural world and human behavior. In our not so distant past, a wealth of new measures emerged and it became clear that the body and mind were intimately linked. Brain research flourished, and people began to construct biological theories about the mind and test them using scientific methods. At this time the scholars applied a new set of interesting tools to help try to make sense of our remarkable brains. Today we have a wide array of incredible tools with which to investigate our thinking and reasoning processes. We do so in the context of both biology and psychology. This book describes many of the breakthroughs that have led to our current thinking on the topic of reasoning in relation to the mind and brain.

Writing a book is a vast undertaking, and this may be particularly true about a book on reasoning. There are still many unknowns in this field. We do not fully understand how different cognitive processes are defined at the level of the brain. We do not yet have methods that allow us to record from large enough populations of neurons across the brain. We cannot yet read neural codes to understand what areas of the brain are actually signaling to one another when information is relayed across the cortex. We do not yet have a strong enough grasp on which cognitive processes are involved in which types of reasoning. Added to these challenges is the fact that reasoning occurs in a dynamic way. Thoughts occur to us seemingly out of the blue. We connect ideas together because we notice events occurring in a particular order. We make errors in our inference and quickly correct them. When we gain expertise in an area, we have a difficult time describing to a novice how we are accomplishing our plans in what appears to be a remarkably fast and efficient way to the beginner. Due to these challenges and limitations the field remains quite diverse. There is always more research to be done.

The challenges in studying reasoning may stem from the fact that we are ultimately limited by our own reasoning processes in how we study the topic. Reasoning emerges out of a remarkably complex series of events that we can only glimpse at with the current technology. The brain is a classic example of a complex system, and reasoning must be examined from a certain point of view or level of analysis. We cannot hope to understand it from a purely top-down perspective, using our own introspection to look inward upon our thought processes. Likewise, we cannot view it from a purely bottom-up perspective by examining the biochemistry of the brain and attempting to grasp our thinking at the level of neurochemical activity. Understanding reasoning requires a balanced viewpoint. We must take a top-down approach to define a limited aspect of cognitive processing constrained to certain circumstances and combine this with a bottom-up view that is informed by our growing knowledge of neuroscience. Because our top-down definitions can be imprecise and there remain many gaps in our understanding of the brain, there are no easy answers in this field.

This book will walk you through some of the major steps on the journey toward understanding thinking, reasoning, and decision making. We will examine these topics from a series of different perspectives. Together, the chapters add up to inform the reader about the current state of the field, how we got to where we are now, and possibly where we are going as new methods develop and technological capabilities begin to approach human levels of capacity on certain tasks.

Features of the Book

Each chapter features research that is organized around a core topic. The topic serves as an anchor point or general domain, but remember that this is all about thinking and reasoning. Due to the sheer diversity of research that makes up this fascinating field, there is a rather wide distribution of research topics and themes in each chapter. Rather than focus on every topic and provide a very detailed and complete description of that specific area, the chapters emphasize providing an overview, or survey, of several aspects of each topic. I will freely admit that no book on this topic can hope to offer a complete guide to reasoning. There is simply too much research in too many disciplines in this field to achieve such a goal. Therefore, I offer you, the reader, a flavor of some of the important research in each area and invite you to dig deeper and search the relevant literature in the areas that you find captivating.

The book is organized in a bottom-up manner. We will begin with basic definitions of reasoning presented in this chapter. From there we will proceed to examine reasoning from a historical perspective in Chapter 2. I felt this was important to set the stage and offer context to the topics that come later. To appreciate the research in this field, one has to have a sense of its context, what was going on during different time periods, and why certain conclusions were drawn. We then move to an introduction to the study of reasoning from the perspective of neuroscience. This chapter offers the reader a sense of the growing body of work connecting the mind to the brain. This chapter may be easier to follow if you have had a course in an area of neuroscience, but I have not assumed an extensive neuroscience background and have constructed it in a way that should make sense to a diverse audience. Our reasoning and thought processes are shaped by our nervous system and the experiences we have had in life. Having a grasp of the types of neuroscience research currently available will help the reader to follow much of the content in the later chapters, all of which include some elements of neuroscience. Chapter 4 examines the fascinating field of animal reasoning research. From there, we move through the lifespan in Chapters 5 and 6 beginning with reasoning in young children, moving through adolescence, and lastly examining reasoning in older adults. Chapter 7 complements the previous three chapters by discussing the impact of neurological and psychiatric disorders on reasoning. Chapter 7 includes extensive information about the brain and many disorders that impact people throughout the lifespan. Chapters 8–11 discuss different categories of reasoning, such as deduction, induction, reasoning about contingencies and causes, analogical reasoning, and how we make decisions. The final chapters take a broader view examining how we reason within the context of society and the impact of technology on reasoning.

Throughout the book I invite the reader to identify consistencies and areas of overlap among the topics presented. The discipline of reasoning has blurry edges. Research does not always fit neatly under one particular theme or area. There are times where the same cognitive processes that constrain reasoning in young children also impact older adults. There are situations in which historical concepts from ancient philosophy are studied using modern brain imaging techniques. There are also domains of research that fall well outside of psychology, neuroscience, or biology that strongly impact the topic of reasoning. The development of computers is one such area. Because of these overlapping conceptual frameworks, I encourage the reader to take an active role in noticing the connections that occur in the research from chapter to chapter. I have tried whenever possible to refer the reader to other chapters in the book that have strong conceptual overlap with a given topic. This overlap at times makes content within multiple chapters merge, but I suppose that is just a part of making sense of a diverse and evolving field of study.

The chapters all contain a mix of research from different disciplines and historical periods. This differentiates the text from other neuroscience books on offer. Some chapters focus heavily on the constraints on reasoning imposed by the brain. Other chapters focus on research at the level of conceptual thought, memory, and human behavior. This diversity reflects a core feature of reasoning research. Few other disciplines within research on the mind and brain are so defined by the context and a confluence of multiple cognitive operations. Throughout the reference sections of each chapter you will notice research spanning a wide period of time. This reflects the evolution of our field. For example some of the core research on deductive reasoning took place over 50  years ago. There have been improvements in our understanding and expanded methodology, but one has to view the research with an understanding of what had been accomplished during the peak periods of discovery. There are times when the chapters will introduce concepts from diverse disciplines. For instance we benefit greatly from the perspective of evolutionary biology when we consider some aspects of complex behavior in animals. We need to understand that perspective to decide if those behaviors should be defined as reasoning. We also rely upon work from behavioral economics in order to understand social aspects of decision making. Throughout the book I have attempted to offer the reader some of these diverse perspectives that connect to further inform our understanding of reasoning and decision making.

Each chapter begins with a section describing key themes. These are helpful hints previewing some of the major areas associated with each chapter. Readers may find it helpful to read the key themes over before reading the chapter. Likewise, it may be helpful to reread these in association with the summaries at the end of each chapter, as they will recap major ideas that were covered.

All of the chapters contain boxes, which are independent sections that present a different perspective on a topic relevant to reasoning. Each box is intended to complement the material covered in the sections surrounding it. These can be read in sequence with the text, or may be better read after completing a surrounding section of the chapter. Reasoning is very much a daily life activity that is most interesting and engaging when placed into a specific context. The boxes are all self-contained and many of them present unique, engaging, or fun examples of the lessons of reasoning as they are carried out in our daily lives, or at some interesting point in the history of the field.

Each chapter concludes with a series of end-of-chapter thought questions. These questions are intended to stimulate further thought in the reader. There may be clear answers to some of these questions after reading the chapter, while others may force you to ponder over them for some time. For some thought questions, we may not yet have answers, but further research into the area may prove fruitful. All references are provided at the end of each chapter, and I encourage the reader to look these papers up and read them if you feel inspired. There is no substitute for reading the original sources as they appeared in the literature and framed in the context in which the authors originally presented their work.

Defining Reasoning

What Counts as Reasoning?

Everyone has some general sense of what reasoning entails. We have all heard this term in a wide variety of contexts across various aspects of our lives. Other terms such as thinking, pondering, problem-solving, and decision making are frequently interchanged for reasoning. When I tell people that I study reasoning, I often feel that is just not descriptive enough as a stand-alone statement. I usually feel I have to follow-up immediately by stating what that really means in the constrained and limited context of the research lab. The topic of reasoning is taught in schools and at the college level. Again, defining what we mean by reasoning appears warranted in these contexts as well. A psychology of reasoning class is likely to be very different than a philosophy of logic class or a scientific reasoning class taught through a chemistry or biology department. Lastly, a literature search for reasoning articles may yield artificial intelligence papers, engineering papers, developmental psychology papers, and clinical assessment articles. Again, a clear definition is called for.

For the purposes of this book and more broadly for the actual study of reasoning in human participants within a laboratory environment, I will define reasoning according to three characteristics. There are certainly other definitions possible, but I believe these three features capture the essence of what most of us mean when we use the term reasoning. You can think of these as the A, B, and C of reasoning:

A. Reasoning uses multiple inputs to produce one output. That output can emerge in the form of a physical action or simply a new thought that emerges from mental processing.

B. Reasoning involves multiple steps. It is helpful to think of these steps as occurring within a space. There may be multiple routes through the space toward an output. Reasoning has individual elements that often form sequences.

C. Reasoning is a hybrid. It relies upon a combination of prior knowledge and new information. Some outputs follow from the novel combination of multiple elements of prior knowledge. Some outputs follow mostly from assembling new elements of information.

Let’s consider each of these characteristics in a bit more detail beginning with A, reasoning uses multiple inputs to produce one output. It is critical that there be multiple inputs into a reasoning process. Reasoning takes in a wider set of premises, conditions, or possibilities and transforms or distills these into one output. There are many behaviors that are evoked by a single input, but these do not qualify as reasoning. The sensation of pain makes us withdraw our hand. The visual input of an oncoming snowball makes us duck. The sight of a green traffic signal leads us to drive forward. These are somewhat complex behaviors, especially when one considers how they are carried out at the level of the nervous system. Most of us would call withdrawing our hand due to pain, or ducking from an oncoming projectile, to be reflexes. These behaviors do not involve conscious deliberation. We simply act before we have taken the time to assess the situation. Deciding to drive forward in response to a green light is probably a better fit to the category of learned behavior. We rarely find ourselves pondering whether to go or remain stationary in response to the traffic signal. It is not a good example of a reasoning task (Fig. 1.1).

Meanwhile, imagine that you are a new driver and are not familiar with the meaning of the lights. Many of us have had some situation like this when visiting a foreign country and looking at a road sign. In this situation, we take in several inputs (the visual elements of the sign, the placement of the sign, the physical surroundings, etc.), and we attempt to find a single output to the best of our abilities (stop, go, pause, etc.). The output may be spot on. We drive our rental car forward after a short pause and receive positive feedback in the form of not causing an accident or making anyone angry. At this point we have learned something new and with enough repetition of encountering this novel sign and repeating the successful drive forward after pausing behavior, we can move this scenario on into the learned behaviors section of our mental lives. Imagine instead that you drive forward in response to this sign and are met with other oncoming vehicles blocking your path and pedestrians looking at you with irritable expressions. This feedback suggests that your output was incorrect. You’ll have to try reasoning again, this time integrating the newly acquired negative feedback into your approach and narrowing down your search for a solution by excluding the faulty drive forward possibility.

Figure 1.1  Deciding how to respond to a stimulus in the environment depends on our familiarity with it. When we are highly familiar with a traffic signal, then our response is a learned behavior. If we are unfamiliar, such as when visiting a foreign country, we may have to reason in order to discover the appropriate action that is signaled. From Wikimedia Commons.

You could take issue with the idea that reasoning involves only one output. Why not several outputs? This becomes somewhat tricky. There can be situations in complex reasoning, in which the output may be to carry out a particular sequence of multiple steps and in some specified order. I would argue that this happens in daily life through the process of iterative reasoning in which we have carried out several acts of reasoning and then assembled the outputs of those independent acts in order to accomplish something greater. I maintain that reasoning moves from multiple elements of information toward a single action or conclusion. That action, or conclusion, can be nuanced and have its own conditional qualities, but reasoning rarely involves multiplying information into many conclusions. Such an act of thought would probably fall into the topic of idea generation or brainstorming, which we will cover in greater detail in Chapter 12. The process of idea generation almost always follows with a second act, in which we narrow down the numerous candidate ideas according to a rank order and often end up selecting the best single output or solution.

Let’s now further consider B, reasoning involves multiple steps. Reasoning is just not simple. Like my examples of reflexes and learned behaviors, when we can reach an intuitive conclusion, or act without deliberating, then we are not reasoning. Reasoning nearly always involves moving from one consideration to the next, to eventually reach an output. This may be due in part to the characteristics of our brains. We can only process a limited set of information at any one time. In complex environments, such as navigating city streets, we are faced with numerous sensory inputs, moving cars, buses, bikes, and people, along with a complex set of interconnecting streets and visual features. When we add our emotions, time pressure, and goal states to this context, we are simply forced to do things in a sequence. We have limited powers of perception, attention, and memory. The mismatch between an environment loaded with inputs and our limited capacity of information processing results in multiple steps that need to take place for reasoning to occur.

If behaviors occur without multiple steps, then they probably would not count as reasoning. This is again debatable and one would have to consider the specifics of a situation, but I maintain that reasoning involves making transformations to the information that we take in. Taking in inputs and producing them verbatim should be categorized as memory or learning. There must be multiple steps and these often occur flexibly. There is not always one solution to a problem. Rather, as the premises or initial state becomes more complex, we can usually find multiple ways forward toward an acceptable end state.

Researchers in several disciplines have considered state spaces to be helpful ways to analyze problems and to conceptualize the possibilities for different situations. A state space is a helpful spatial analogy with which to describe our mental processing (Fig. 1.2). State spaces are defined as being the set of all possible configurations that a given problem can achieve. This term is used in computer science to analyze software capabilities and in economics to analyze the possible utility, or value, of different possibilities. The analogy between a search space and problem solving highlights the fact that there are many ways to progress toward a solution. A thinker would like to move in a direction that enables the most optimal solution among the possibilities existing in the state space (Zhang, 1999). This captures an essential feature of reasoning: there is not one way to do it. There may not even be a logically correct answer. Through processing and evaluating numerous inputs, we can transform information using a series of steps that move us toward a successful solution. You can think of many examples in which reasoning fails. We try different approaches, but find that we are not successful. Fortunately, reasoning can be iterative, and we can often try again armed with new knowledge and a narrowed search space (with fewer possible routes achieved through the process of elimination).

Figure 1.2  In engineering, state spaces can be represented by mathematical models of a physical system. These include inputs, output, and paths that can be taken. Reasoning can be thought of in terms of a state space that moves us from inputs to an output down a variety of different paths.

Now let’s turn our attention to C, reasoning is a hybrid. There are rare instances in which we reason about unfamiliar information to reach a completely novel conclusion. We may call this approach creative. Reasoning can be heavily weighted toward taking a very new approach and thinking on our feet and making it up as we go along. There are also times when we reason using well-known facts or prior knowledge. Either situation can be defined as reasoning. I would argue that most of the time we reason by combining some degree of previous knowledge with other elements of new information. At minimum, we must assemble previous knowledge elements in a novel way for a mental process to qualify as reasoning. Almost any time we are operating with new information, we will consider that to be reasoning as well. Complexity is inherent in feature C of the definition. Reasoning cannot involve the simple output of previous knowledge, or it reduces to a learned behavior, or possibly even a reflexive behavior. Implicit memories (Knowlton, Mangels, & Squire, 1996) would not count as reasoning for most of us, as they evoke a behavior without deliberation or the necessary complexity. Rather, they are classic examples of learning.

Factors That Influence Reasoning

We can also consider some other important mediating factors when we define a behavior as being an act of reasoning. One of these factors is the biology of an organism. We are not purely agnostic information processors. While we can attempt to work toward an optimal solution, we have drive states that govern our thinking. Simple states such as pain, satiety, hunger, and thirst can dominate our thinking and dictate our next behavior. The need to interact with others influences us. We can gain by making other people happy. Seeking social rewards such as recognition, approval, and the acceptance of others limits people from acting in a purely selfish manner (Fig. 1.3). We will discuss social reasoning situations in detail in Chapter 12. Furthermore, our needs can evolve as we age and develop our knowledge through experience. Hormone levels are another biological factor that can influence reasoning and behavior. We may reason purely based on information, but many times our desired outputs or solutions are intertwined with our biological needs and drive states.

Our cognitive capacities also strongly influence our reasoning abilities. Our limited mental resources prevent us from being purely rational thinkers. Consider attention as an example. Classic research demonstrating the concept of change blindness indicates that people have a very difficult time noticing a change in visual features present in two images presented directly one after another (Simons & Levin, 1997). For example, if you look at the images in Fig. 1.4 you may have to alternate back and forth several times before you notice the change. Go ahead and try this short demonstration for yourself. The fact that we cannot quickly isolate the change in visual features indicates that our attention has limitations (part of the letter on the right lower half of the field has changed from blue to gray). This means that we can only take in some of our visual environment at any given time. Similarly, we can only focus on a few memories from our lives in a detailed way before we become overwhelmed. Once we attend to information we can move it into a short-term store of information often referred to as working memory (Baddeley, 1986). Our working memory capacity is limited, and we simply cannot add more into our buffers. This limitation can be overcome to some degree by performing an operation known as chunking. When we chunk information we can use our long-term memory to group sets of objects, events, or locations into a set, effectively expanding our active working memory capacity. There is no getting around the limits of our cognition. If we cannot fully perceive or attend to all possible information, then our reasoning will suffer as a result.

Figure 1.3  We seek social rewards including recognition, approval, and the acceptance of others. These incentives influence our reasoning when other people are involved. From Shutterstock.com

The topic of limited mental resources leads us to another relevant capacity for reasoning and that is consciousness. Many people would consider the act of deliberating about a topic to be the essence of reasoning. The extended consciousness of humans enables us to enrich our mental representations and examine their contents. We can consciously imagine future states of the world, reflect on previous situations, cue our own memories of the past, and in doing so discover novel connections relevant to a problem. This is often thought to be a dividing line among different species. Is consciousness necessary for reasoning? I would argue that it is not necessary, although it does increasingly accompany acts of reasoning as it becomes complex and probably occurs to a greater extent in species with large and complex nervous systems. Consciousness may help or inhibit our efforts in reasoning. The fact remains that all species have limitations of consciousness and many aspects of our mental processing occur without our conscious supervision. Similarly, it is difficult to find a clear role for consciousness in acts of reasoning carried out by computers (although they have a strong helping hand from conscious human programmers!).

Figure 1.4  Can you spot the change between these two images? Change blindness occurs when we fail to notice a change in a visual feature between two images presented directly one after another.

The brain may be the final arbiter of reasoning ability. As we will see in the coming chapters, the characteristics of our brains heavily shape our reasoning. This becomes evident when we examine reasoning across the childhood years. The reasoning of very young children lacks the benefit of experience and brain maturation. The very young tend to be self-focused in their thinking. Most situations are novel to them, they are highly emotional, and they are driven by impulses that differ from older children and adults. There is great biological change and brain change over the course of childhood, and we will discuss these aspects of reasoning in Chapter 5. Our reasoning skills can also be directly compromised by disruption to our brains. Strokes and brain injuries to particular locations will reliably impair our power of reason. Some types of brain damage affect our emotional processing and change the drive states and impulsivity levels of a thinker. Reliably different behaviors and outputs occur in such individuals. Reasoning impairments can also follow damage to the white matter of the brain, which enables regions to communicate effectively. This can occur because of aging or injury and may lead to slower processing, which compromises attention and working memory resources and thereby limits the number of inputs that can be perceived and considered in solving a problem.

How We Study Reasoning

Historical Considerations

One of the first perspectives presented in Chapter 2 is an overview of the history of reasoning research. It is necessary in any field to have a sense of how we got to the current state of knowledge. We can learn much about the evolving definition of reasoning by examining the way people conceptualized this topic in the past. We can also gain a valuable perspective by noticing how the development of new methods in science has changed our thinking. Throughout the history of reasoning the state-of-the-art has depended upon the methods that were available at the time. Early philosophers were equipped only with their conscious awareness of the inputs and outputs of their thinking. They could categorize reasoning based almost entirely upon the subjective qualities and conceptual basis of the tasks. A new set of measures became possible and theories of human reasoning changed dramatically as the field adopted the methods of experimental psychology. Fascinating research comparing humans to other species has occurred for centuries. The work of comparative psychologists and ethologists further changed the way the field thinks about reasoning. Eventually we entered into an age in which neuroscience and information processing dominate our thinking on the topic of reasoning. Technological developments have made it possible to image the brains of individuals as they think and have enabled researchers to develop machines that reason. These machines may not be conscious, but computers can now process information with remarkable speed and accuracy far exceeding that of human processing in many cases. We must remain aware that humans still program machines and must set up the conditions for machine-assisted reasoning. As we will discuss in Chapter 13, machines are evolving to the point at which they can outperform even expert humans at many rule-based reasoning tasks.

A Multidisciplinary Approach

The text is largely written from my own perspective. I am a cognitive neuroscientist. In my undergraduate years I studied psychology and biology. My PhD is from an experimental psychology area and I did postdoctoral training with a cognitive neurologist studying brain imaging methods as they apply to human cognition. My current academic position enables me to regularly interact with a diverse set of scholars including developmental psychologists, social psychologists, behavioral economists, neurologists, psychiatrists, neurobiologists, and rehabilitation specialists. I believe this lack of strong disciplinary boundaries is helpful for the study of reasoning. I have gained from the wealth of different methods and perspectives that I am exposed to, and I believe this shows in the chapters of this book.

It takes a village to study reasoning. You will find that we cover each topic from a variety of perspectives. I find biology to be particularly useful in describing the reasoning behavior of other species. In some of the chapters, economic perspectives are particularly valuable for describing social aspects of reasoning and how we decide under uncertain conditions. Developmental psychology and gerontology offer incredibly rich perspectives on the changes in reasoning observed through the lifespan. Cognitive psychology helps to delineate the important mental operations that underlie reasoning abilities. At the core of all of these perspectives is neuroscience. The brain characteristics of humans and other species are central to all of the reasoning capacities that we observe in the natural world. Even computerized reasoning operations are heavily informed by the information processing approach that is used by the biological neural networks of the brain.

Categorizing Reasoning

Defining Diverse Modes of Thinking

Before we proceed on to the content areas of the book, it is worth considering some of the different categories of reasoning. The first several chapters (Chapters 2–7) cover topics including the history of reasoning research, the neuroscience of reasoning, the reasoning of other species, and lifespan approaches to reasoning. Since these chapters focus on specific characteristics of particular groups of people and organisms that reason, it may be helpful to foreground some of the major categories of reasoning that are agreed upon within the field. Many of these categories will be discussed in advance of the later chapters that more exclusively focus on each category of reasoning. These categories are summarized in Box 1.1.

Determining Cause and Effect

Causal reasoning is the process by which we establish cause-and-effect relationships between two or more entities. This can be as simple as inferring that a marble moving toward another marble caused the second marble to move after colliding. Although the causal attribution feels almost perceptual, it is not a trivial inference. Likewise, people draw a causal association between thunder and lightning due to their co-occurrence in time; however many people remain fuzzy on the actual mechanistic relationship between these features of a storm. Causal reasoning enables us to isolate causes and effects in more complicated situations as well. Detectives regularly have to establish the most plausible explanation for who caused a crime to happen. Our entire legal system is based upon causal relationships between actions and outcomes. We will discuss causal reasoning in animals in Chapter 4 and cover the topic in greater breadth and depth in Chapter 8.

Reasoning About Rules

Very early in the history of human thinking philosophers considered the validity or soundness of conclusions. The method of deduction allows a thinker to move from a set of inputs called premises toward a specific output or conclusion. The premises set the rules for the deductive process. Deductive reasoning yields a valid conclusion provided that it has been carried out effectively. As we will discuss in Chapter 3, there are neuroscience studies of deduction that help to inform us about the brain basis for this process. In Chapter 9 we will discuss how people reason deductively and compare this to inductive reasoning.

Box 1.1

Categories of Reasoning

This list of areas of reasoning will occur throughout the book. Below are some basic definitions you may find useful to refer to.

• Abductive reasoning: Abduction refers to a situation in which we do not have all of the possible information available as premises or inputs. Abduction involves reasoning to the best possible output or explanation without having all of the information necessary to yield an objectively correct output.

• Analogical reasoning: Analogical reasoning involves using relational information about a known situation and applying that set of information toward a new situation that shares relational similarity. Drawing an inference on the basis of shared relations is a type of inductive inference.

• Causal reasoning: The process by which we establish cause-and-effect relationships between two or more entities.

• Decision making: An area of study that focuses on how we arrive at a single choice among other options. Decision making and reasoning are highly interrelated.

• Deductive reasoning: Reasoning from a set of inputs called premises toward a specific output or conclusion. The premises set the rules for the deductive process. Deductive reasoning yields a valid conclusion provided that it has been carried out effectively.

• Insight: Insight describes a feeling of confidence that we have discovered a novel and creative answer to a problem.

• Inductive reasoning: Reasoning about a situation in which we draw a general inference about a set of items on the basis of a limited set of premises. Unlike deduction, inductive inferences are not guaranteed to be valid.

• Relational reasoning: The term relational refers to the way that multiple items are interrelated. Relational reasoning is concerned with the relational connections among objects, or items.

• Social reasoning: This term describes any situation in which we reason about a social situation involving other people. It can include cooperating with others or competing against them in order to generate an output, or solution.

Inductive Inferences

Much of our reasoning involves using our knowledge about specific examples to draw conclusions about a wider set of items that we see as occupying that same category. This is inductive reasoning, a situation in which we draw a general inference about a set of items on the basis of a limited set of premises. Induction is discussed with regard to the brain in Chapter 3 and again in more detail in Chapter 9. Analogical reasoning involves using relational information about a known situation and applying that set of information toward a new situation that shares relational similarity. The term relational refers to aspects of multiple items and how they are interrelated. For example, terms such as above, below, causes, kisses, and helps are all relational, as they describe a type of action or connection that occurs between two or more people, objects, or items. Drawing an inference on the basis of shared relations is a type of inductive inference. We discuss relational reasoning throughout this book. We emphasize analogical reasoning in Chapter 3 by discussing relevant neuroscience research. We discuss the topic of analogical reasoning again in Chapter 5; in Chapter 7 we discuss disorders of reasoning and in Chapter 10 we discuss in depth this form of reasoning.

Reasoning and Decision Making

Reasoning and decision making are often linked under the broader heading higher cognition. Decision making also fits parts A, B, and C of the definition for reasoning that I provided in this chapter. Decisions almost always involve multiple inputs in the form of choice options or multiple attributes of the options and result in one output, the decision in favor of one or more options. Decision making is also a multiple step process with a state space that is not predefined. Rather we work toward an optimized decision from the possible choices. Decision making involves some hybrid characteristics combining new information with previous knowledge. Chapters 2, 3, 5–7 all cover aspects of decision making. While Chapter 11 is fully devoted to this topic, we will revisit decision making again in Chapter 12 covering social reasoning.

Putting it All Together

Reasoning in Society

Reasoning can become even more complex and interesting in the context of other people. As we will discuss in Chapter 3, animals can reason in groups both benefiting and competing with one another. People also influence one another’s reasoning. In Chapter 12 we will discuss social reasoning, which pertains to the way that people reason with one another, sometimes deciding to compete and other times cooperating. We will also focus on group reasoning in this chapter. Sometimes we benefit from a group effort, while other times we create conflicts when we think in groups.

What Does the Future Hold?

We will conclude the book with a discussion of the role of technology in reasoning. A particularly innovative and exciting part of the field is focused on using new methods in computing to augment, or expand, human reasoning capabilities. In the past several decades we have witnessed unparalleled advances in computer processing power and software sophistication. Now computers programmed to reason against human experts can dominate even the most astute humans in some of the most complex games of advanced reasoning. Interestingly, the act of building intelligent machines continues to tell us a great deal about the nature of reasoning and even about how the brain may operate as well. Chapter 13 covers new directions in technologically enhanced reasoning.

Summary

Reasoning is a complex and multidisciplinary area of study. This book presents a series of overviews of an array of topics in the field. The book proceeds in a bottom-up manner by first introducing research on the brain and reasoning and working up toward social aspects of reasoning and the impacts of technology. Along the way we will cover many categories of reasoning and consider the implications of the nervous system, development, aging, and brain injury on reasoning.

Reasoning involves some core features. Three important aspects of reasoning were discussed in this chapter. First, reasoning involves moving from multiple inputs to a single output, which can be a conclusion or an action. Second, reasoning involves multiple steps through a state space to achieve a final outcome. There are numerous ways through the process to achieve different outputs. Third, reasoning involves a mixture of previous knowledge combined with novel information. The precise combination of these types of information will vary based on the type of problem.

Reasoning is a fascinating topic of study. The research community must take a broad view and incorporate many research methods to understand the process. It is also important that researchers propose clear operational definitions of the reasoning type that they are planning to study. The future of reasoning research looks bright with exciting new methods advances occurring regularly, along with innovative developments in technology.

End-of-Chapter Thought Questions

1. The study of reasoning is a multidisciplinary area. Which academic disciplines do you most associate with the study of reasoning? Are there cases in which two or more disciplines essentially study the same topic?

2. Reasoning involves moving from multiple inputs to a single output, which can be a conclusion or an action. Think of how this applies to a simple reasoning task and a complex one. Does this aspect of the definition apply to both?

3. Reasoning involves multiple steps through a state space to achieve a final outcome. Does the state space idea work better for simpler acts