Table of Contents – Instructor’s Resource Manual
TopicPage
Prefaceix
Chapter 1 – How the Brain Gives Rise to the Mind
Chapter Learning Objectives1
Class Lecture Leads
Artificial Intelligence1
Action Potentials4
The Limbic System5
Placebo Effects7
Featured Classroom Activity
Brain Functions9
Annotated List of Additional Resources
A Brief History: How We Got Here10
Understanding the Mind: The Form of Theories of Cognition11
The Cognitive Brain12
Studying Cognition12
Handout 1a15
Handout 1b16
Handout 1c17
Handout 1d18
Handout 1e19
Handout 1f20
Handout 1g21
Chapter 2 – Perception
Chapter Learning Objectives23
Class Lecture Leads
Color versus Black and White (Light and Dark) Vision23
Different Types of Agnosia25
Figure/Ground Parsing27
Cues for Depth Perception29
Featured Classroom Activity
Effects of Top-down Processing and Schemas31
Annotated List of Additional Resources
What it Means to Perceive33
How it Works: The Case of Visual Perception33
Building from the Bottom-Up: From Features to Objects34
Achieving Visual Recognition: Have I Seen You Before?35
Interpreting from the Top-Down: What You Know Guides What You See35
In Models and Brains: The Interactive Nature of Perception36
Handout 2a38
Handout 2b39
Handout 2c40
Handout 2d41
Chapter 3 – Attention
Chapter Learning Objectives43
Class Lecture Leads
Artificial Attention Deficit (hyperactivity) Disorder43
Signal Detection Theory: Attention Mechanisms46
Automaticity47
Divided Attention48
Featured Classroom Activity
Automatic Processing50
Annotated List of Additional Resources
The Nature and Roles of Attention51
Explaining Attention: Information–Processing Theories 54
Looking to the Brain56
Competition: A Single Explanatory Framework for Attention?57
Handout 3a57
Handout 3b58
Chapter 4 – Representation and Knowledge in Long-Term Memory
Chapter Learning Objectives59
Class Lecture Leads
Analogue Representations in Mental Imagery59
Mental Rotation61
Schemas62
Association Areas of the Brain63
Featured Classroom Activity
Categorization as a Memory Tool64
Annotated List of Additional Resources
The Roles of Knowledge in Cognition66
Representations and Their Formats66
Form Representation to Category Knowledge67
Structures in Category Knowledge68
Category Domains and Organization69
Handout 4a71
Chapter 5 – Encoding and Retrieval from Long-Term Memory
Chapter Learning Objectives73
Class Lecture Leads
Learning Theories74
Explicit and Implicit Types of Long-term Memory76
Forgetting: Infantile Amnesia77
Episodic Memory: Source and Flashbulb Memories78
Featured Classroom Activity
Reconstructive Memory80
Annotated List of Additional Resources
The Nature of Long-Term Memory82
Encoding: How Episodic Memories are Formed85
Retrieval: How We Recall the Past from Episodic Memory86
The Encoding was Successful, But I still Can’t Remember88
Nondeclarative Memory Systems89
Handout 5a90
Chapter 6 – Working Memory
Chapter Learning Objectives91
Class Lecture Leads
Levels of Processing91
Mnemonic Devices93
Structures of the Brain and Memory95
Dual-coding96
Featured Classroom Activity
The Serial Position Curve97
Annotated List of Additional Resources
Using Working Memory99
From Primary Memory to Working Memory: A Brief History101
Understanding the Working Memory Model103
How Working Memory Works104
Current Directions105
Handout 6a107
Chapter 7 – Executive Processes
Chapter Learning Objectives109
Class Lecture Leads
Frontal Lobe Damage and Disorders109
Phineas Gage111
Stimulus-Response Compatibility113
Monitoring and Executive Processes114
Featured Classroom Activity
Monitoring Working Memory115
Annotated List of Additional Resources
The Frontal Lobe Connection117
Frontal Damage and the Frontal Hypothesis119
Executive Attention119
Switching Attention121
Inhibition of Response122
Sequencing122
Monitoring123
Handout 7a124
Handout 7b125
Handout 7c126
Handout 7d127
Handout 7e128
Handout 7f129
Chapter 8 – Emotion and Cognition
Chapter Learning Objectives131
Class Lecture Leads
Emotion and Automatic Processes131
Observational Learning134
Mood-Congruent Memory Effect136
Six Basic Emotions137
Featured Classroom Activity
Six Basic Emotions138
Annotated List of Additional Resources
The Connection140
Defining Emotion141
Manipulating and Measuring Emotion142
Emotional Learning: Acquiring Evaluations143
Emotion and Declarative Memory145
Emotion, Attention, and Perception147
Handout 8a149
Chapter 9 – Decision Making
Chapter Learning Objectives151
Class Lecture Leads
Heuristics as Biases151
Alternative: Multiattribute Decision Making154
Risk156
Framing Effects157
Featured Classroom Activity
Risky Decisions159
Annotated List of Additional Resources
The Nature of a Decision160
Rational Decision Making: The Expected Utility Model161
Neural Bases of Expected Utility Calculations163
Human Decision Making and The Expected Utility Model: How
Close a Fit?163
Complex, Uncertain Decision Making166
Handout 9a167
Chapter 10 – Problem Solving and Reasoning
Chapter Learning Objectives169
Class Lecture Leads
Impediments to Problem Solving170
Problem Solving Strategies171
Insight174
Probability and Problem Solving175
Featured Classroom Activity
Nine-dot Problem177
Annotated List of Additional Resources
The Nature of Problem Solving178
Analogical Reasoning182
Inductive Reasoning182
Deductive Reasoning183
Handout 10a186
Handout 10b187
Chapter 11 – Motor Cognition and Mental Simulation
Chapter Learning Objectives189
Class Lecture Leads
Mental Rotation189
Apraxia191
Mirror Neurons192
Biological Motion193
Featured Classroom Activity
Mental Rotation196
Annotated List of Additional Resources
The Nature of Motor Cognition197
Mental Simulation and the Motor System200
Imitation203
Biological Motion206
Handout 11a208
Handout 11b211
Chapter 12 – Language
Chapter Learning Objectives213
Class Lecture Leads
Bilingualism213
Language Production Errors215
Aphasia and Language216
Development of Language218
Featured Classroom Activity
Figurative Speech and Idioms220
Annotated List of Additional Resources
The Nature of Language222
Processes of Language Comprehension226
Processes of Language Production229
Language, Thought, and Bilingualism231
Handout 12a233
Handout 12b236
Table of Contents – Test Bank
TopicPage
Chapter 1: How the Brain Gives Rise to the Mind239
Chapter 2: Perception267
Chapter 3: Attention291
Chapter 4: Representation and Knowledge in Long-Term Memory317
Chapter 5: Encoding and Retrieval from Long-Term Memory337
Chapter 6: Working Memory359
Chapter 7: Executive Processes379
Chapter 8: Emotion and Cognition399
Chapter 9: Decision Making417
Chapter 10: Problem Solving and Reasoning437
Chapter 11: Motor Cognition and Mental Simulation457
Chapter 12: Language477
Appendix: Total Assessment Guides497
Preface
This Instructor’s Resource Manual is designed to accompany Cognitive Psychology, First Edition, by Edward E. Smith and Stephen M. Kosslyn. This manual has the student in mind in its design, content, and approach, while facilitating ease of usage for the instructor. This package includes all materials, including supplementary materials, needed to facilitate insightful discussions and creative classroom activities related to topics covered in the text.
Organization:
The organization of the Instructor’s Resource Manual is by textbook chapter. Each chapter in the manual has five parts: Chapter Learning Objectives, Class Lecture Leads, Featured Classroom Activity, Annotated List of Resources, and Handouts for the Featured Classroom Activity.
Chapter Learning Objectives
Each chapter in the manual begins with a list of Chapter Learning Objectives. These learning objectives are key points, terms, and/or ideas that the student should comprehend as they read the chapter. They mark the most important concepts of each chapter. Page numbers, where the concepts can be found, are listed after each objective in parentheses.
Class Lecture Leads
Each chapter in the manual includes four Class Lecture Leads. These lecture leads are intended to reinforce, and in many cases, be supplementary to topics covered within the text chapter. Because the instructor already has many of the text concepts at his or her disposal, the class lecture leads are intended to add or build upon many of the textbook ideas. They are short and concise summaries of four topics per chapter, meant to provide “leads” for the instructor to prepare lectures.
Featured Classroom Activity
One classroom activity per chapter is presented. Each activity is related to text topics. Any materials required for the activity (handouts, as well as answer keys) are provided at the end of each chapter section, listed as Handouts. Guidelines and instructions for each activity are provided, enabling instructors to carry out activites in class without much extra preparation required.
Annotated List of Resources
At the end of each chapter section of the manual, a complete list of resources is provided. These resources are in addition to textbook references and should provide extra support for textbook topics and concepts. They are organized by Readings(related books and journal articles), Online Resources (websites that provide extra information or activities), Video (any videos related to textbook material), and Experimental/Interactive (online/disk demonstrations or experiments).
Readings include materials from Current Directions in Cognitive Science, Readings from the American Psychological Society (2005), edited by Barbara Spellman and Daniel Willingham. Videos include resources from the Prentice Hall Video Library, Films for the Humanities and Sciences, Psychology edition. Finally, experimental/interactive resources include Live!Psych Simulations on disk. All other references cited are seminal pieces or from contemporary sources, and will provide a wide range of theories and experiences to supplement the course text.
In conclusion, the Instructor’s Resource Manual is a valuable addendum to the Smith and Kosslyn Cognitive Psychology text. It provides many additional resources that enhance key topics discussed within the text. It is a self-contained toolkit, designed for the instructor to assist in preparing lectures, classroom activities, and discussion.
Melissa S. Terlecki, PhD.
1
Chapter 1 – How the Brain Gives Rise to the Mind
Chapter Learning Objectives:
- Explain what cognitive psychology is (pp. 2-3).
- Explain who was involved in the early evolution of cognitive psychology, from philosophy to introspection to behaviorism (pp. 3-7).
- Understand how and why the cognitive movement was predicated upon computers (pp. 7-11).
- Explain what mental representation and mental processing are (pp. 11-13).
- Understand what the structure-process trade-off is, including the difference between serial and parallel processing (pp. 13-15).
- Identify the structures of cognitive brain; from the most basic parts of the neuron to the structure of the nervous system, the lobes of the cerebral cortex and subcortical structures (pp. 17-24).
- Compare the different types of neurons (sensory neurons, motor neurons, interneurons, glial cells) (p. 17).
- Understand how dissociations and associations are critical for studying cognition (pp. 25-26).
- Identify the different behavioral methods of measurement (p. 27).
- Identify the different correlational neuroimaging techniques and their spatial and temporal resolutions (p. 30).
- Identify what causal neural methods are available and how they work (pp. 36-40).
- Compare computer simulation, process, and neural-network models (pp. 40-43).
Class Lecture Leads:
Artificial Intelligence
Artificial intelligence is a field that involves an attempt to mimic human cognition in computers with artificial systems. Because computers must be programmed and cannot originate the processing of information on their own, it is remarkable that researchers can create systems that produce the same “output” as humans. Today’s computers have applications across a wide range of problem solving; from nuclear war to everyday problems such as balancing a checkbook. Innovations of artificial intelligence actually began quite some time ago with very rudimentary theories and functions.
Many ancient Greek myths involved uses of mechanical toys and models, which were constructed to mimic real human behavior. In the 13th century, “talking heads” or puppets were created for the pleasure of entertainment. More importantly, and more like modern-day computers and calculators, the invention of the printing press with moveable type was invented in the 15th century. Around the same time, clocks were being produced and later, even extended the craft with the inclusion of movable figurines that were set into motion with the hour. Their movements were to mimic human behavior.
During the 17th century, Pascal created the first mechanical calculator (1642) and Leibniz enhanced the machine to include multiplication and division (1673). Although the 18th century was focused on the further creation of mechanical toys, Charles Babbage and colleague Ada Byron brought us the first rudimentary computer, which was actually the first programmable calculator. The 20th century brought many publications of theories of artificial intelligence,with many prophesizing the future of a mechanized and computerized world (Newell, 1977). The 20th century also brought the first mention of the “robot” (1923). During this time, researchers were beginning to ask if human and artificial intelligence were truly the same.
Alan Turing (1950) was one of the first to test whether artificial intelligence was as “intelligent” as human intelligence. His experiment was designed to discover whether a human could distinguish between the performance of a computer and a human. A human interrogator could ask a respondent (either a computer or a human, whose identity was hidden) any question he or she wished, and based on either the computer’s or the human’s response, the interrogator had to decide if the answer was given by the computer or by the human. This answer was, and still is not easily solved. Variations of the Turing test continue to be formulated today (see Searle, 1980, among others), and arguments as to whether or not human intelligence is distinct linger on.
More recent programs dedicated to artificial intelligence involving the simulation of expertise have proven superior (such as the 1997 chess match between IBM program “Deep Blue” and world champion Gary Kasparov, which ended in Kasparov’s defeat). However, several caveats must still be considered when evaluating the differences and similarities between human and artificial intelligence. First, we must consider the concept of serial versus parallel processing. Humans can efficiently handle the simultaneous processing of several different streams of information, known as parallel processing. It is widely accepted that computers can only handle information (instructions) in a serial fashion (one-at-a-time bits of information), no matter how rapid. However, more recent models that incorporate several networks can process more than one feed simultaneously. Second, some argue that although computers can process symbolic information, they lack intuition or insight; a problem-solving skill that may be distinctly human. Often, intuition or insight comes to us outside of awareness; we cannot explicitly detail how we encountered a solution to a problem, yet we arrive at it. Some argue that because computers need to be programmed for every possible step in a process, they cannot generate solutions that would be novel or intuitive. Can computers go beyond the information given, as humans can? New technologies are breaking the boundaries everyday, and perhaps human and artificial intelligence are becoming closer and closer to being indistinguishable.
Action Potentials
An action potential is what occurs as neurons, cells of the nervous system, pass information along throughout the body. Neurons are electrically charged, and change their charge as information is passed along. At rest, before information is passed through the neuron, the neuron has a negative charge (inside the cell). This is because the cell’s membrane, or outer covering, has selective permeability. At rest, positively charged potassium ions (K+) can flow freely from inside to outside of the cell, but negatively charged chloride (Cl-) and positively charged sodium (Na+) ions have a harder time passing through. Negatively charged proteins inside the cell cannot exit or pass through the neuron’s membrane. At rest, there are more sodium ions outside the neuron and more potassium ions inside (along with the more negative charge because of the stationary proteins). If a message comes along (which is transmitted through a chemical called a neurotransmitter), this resting charge is changed. If the chemical is excitatory, depolarization occurs and the message is sent along, but if the chemical is inhibitory, then the message is not sent along (hyperpolarization). Either way, the change in the charge of the neuron due to excitation would have to be strong enough to reach the neuron’s threshold, which is an individual, minimal level for excitation. The action potential follows an “all-or-none law,” where the neuron either fires (sends the information along) or it doesn’t, and the strength of the firing is the same each time, as long as its threshold has been reached. It fires only if the stimulation causes enough sodium ions to enter the neuron.
Let’s assume that an excitatory neurotransmitter has been passed to a neuron, and the neuron’s threshold has been reached. During this process of depolarization, positively charged sodium ions rush into the neuron. This temporarily changes the charge of the cell from being more negative to more positive (and signals the sending of the neurotransmitter along to the next adjacent neuron).Next, potassium ions rush out, which restores the charge of the neuron (repolarization). This process is a chain-reaction of sorts, as it occurs up and down the length of the neuron’s membrane. This process is also known as the “sodium-potassium pump.” There is a short period where the neuron cannot respond to incoming signals (about 2 ms), and this is called the refractory period because the neuron needs time to restore back to its originally, negatively charged resting state.
Hyperpolarization occurs when the incoming signal is inhibitory and causes the inside of the neuron to become even more negatively charged, and thus prohibiting the action potential from occurring (and the message being passed through the neurotransmitter toward the next neuron).
Action potentials occur all throughout the body in billions of neurons in order to send information from the external world to the internal world and back again. Action potentials are critical for the functioning of the nervous system.
The Limbic System
The limbic system, which was once believed to only regulate emotion, includes structures that serve many other functions. Generally speaking, the limbic system commands cognitions and behaviors necessary for human survival, which include controlling emotion and emotional responses, mood, motivation, pain and pleasure sensations, and some aspects of memory. The limbic system is also responsible for two behaviors exhibited by all mammals; the caring and nursing of females towards their offspring, and playful mood. And although the expression of emotion may differ by culture, it appears that some emotions are universal, including happiness, anger, fear, surprise, sadness, and disgust.
Several theories have been postulated that explain how we experience emotion. The James-Lange theory of emotion (1890) stated that an emotion-invoking stimulus first elicits a body’s physiological response to the arousal, which then in turn leads to a cognitive appraisal of emotion. Later theories by Cannon-Bard (1927) implied that physiological responses are accompanied by one’s emotional experience, simultaneously. Finally, Schacter (1962) proposed a two-factor theory, which stated that a stimulus causes physiological arousal and our creation of a cognitive label for the arousal (e.g., “I am afraid”), which in turn elicits the expression of emotion. Debate continues as to whether or not physiological responses precede cognition and whether cognition precedes emotion, however, it appears that the ability of any theory to explain the experience of emotion depends on the complexity of the emotional response, which varies by type of emotion and individual.