Psych Midterm 1 Review PDF

Psych Midterm 1 Review Chapter 1-5 & Lecture Content WEEK 1 Chapter 1 Learning Objectives How is cognitive psychology relevant to everyday experience? ○ Cognitive psychology is directly relevant to everyday experience because it studies the mental processes that underlie our actions, thoughts, and decisions. It helps us understand how we perceive the world, how we process information, how we remember things, how we solve problems, and how we make decisions. ○ Memory: Cognitive psychology informs how we remember or forget information, which can affect everything from recalling names to remembering appointments. ○ Attention: Understanding attention processes helps explain why we sometimes find it difficult to concentrate or why we can’t focus on multiple things at once. ○ Decision-making and Problem-solving: Cognitive psychology helps us understand how people weigh options, make choices, and solve problems, which is essential for navigating daily life. ○ Language: Cognitive processes are involved in how we communicate, understand language, and interpret messages from others, which is fundamental in social interactions. Essentially, cognitive psychology provides insight into how mental processes impact daily functioning, influencing everything from work performance to personal relationships. How is it possible to study the inner workings of the mind when we can’t really see the mind directly? ○ While we can’t observe the mind directly, cognitive psychology uses various methods to study and infer the workings of the mind based on behavior and physiological responses. Here are some of the ways: ○ Behavioral Experiments: Researchers observe and measure behavior in controlled settings. By analyzing how people react to different stimuli or solve problems, cognitive psychologists can infer the mental processes involved. ○ Neuroimaging: Technologies like fMRI and EEG allow scientists to observe brain activity while participants perform mental tasks, helping to link brain functions to specific cognitive processes. ○ Cognitive Models: Cognitive psychologists develop models of how the mind works, using evidence from experiments to support or refine their theories. These models help explain complex mental tasks such as perception, memory, or decision-making. ○ Self-Report and Surveys: In some cases, researchers gather data on people’s thoughts or experiences through interviews, surveys, or introspective reports, which, when analyzed systematically, provide insight into cognitive processes. ○ Computer Simulations: Researchers use computational models to simulate mental processes like learning or problem-solving, providing insights into how these processes might unfold in the mind. What was the cognitive revolution? ○ The cognitive revolution, which began in the 1950s, was a pivotal shift in psychology that moved away from the behaviorist focus on observable behavior to an emphasis on understanding the mental processes that underlie behavior. This revolution was fueled by several key developments: ○ Criticism of Behaviorism: Behaviorism, which dominated psychology for much of the early 20th century, focused solely on observable behavior and dismissed the study of the mind and internal mental processes. However, researchers like Noam Chomsky critiqued this view, particularly in his famous review of B.F. Skinner’s work on language acquisition, arguing that behaviorism couldn’t adequately explain complex cognitive phenomena like language learning. ○ Advances in Technology: The rise of digital computers provided an analogy for the mind, which was seen as an information-processing system. Researchers like Ulric Neisser and others began to develop models of human cognition based on this analogy, conceptualizing the mind as processing, storing, and retrieving information much like a computer. ○ The Role of Memory and Attention: Experiments on memory, perception, and attention helped establish the idea that mental processes could be studied scientifically. Key experiments by people like George Miller (on the capacity of short-term memory) and Colin Cherry (on auditory attention) showed that cognitive processes could be studied in a rigorous, empirical way. ○ The Rise of Cognitive Neuroscience: The cognitive revolution also paved the way for new technologies like neuroimaging, which allowed scientists to study the brain's involvement in cognitive processes, providing further evidence for the idea that the mind could be understood through scientific study. Test Yourself What are two ways of defining the mind? ○ As a set of mental processes: This includes perception, memory, decision-making, language, and problem-solving, which are the core areas of cognitive psychology. ○ As the system that processes information: The mind is viewed as an information-processing system, much like a computer, receiving input (e.g., sensory data), processing it, and generating output (e.g., thoughts, actions, decisions). Why could we say that Donders and Ebbinghaus were cognitive psychologists, even though in the 19th century there was no field called cognitive psychology? Describe Donders’s experiment and the rationale behind it, and Ebbinghaus’s memory experiments. What do Donders’s and Ebbinghaus’s experiments have in common? ○ Donders and Ebbinghaus were early pioneers of what we now recognize as cognitive psychology, even though the field didn’t exist at the time. They studied mental processes scientifically, laying the groundwork for future cognitive research. Donders’s Experiment: In the 1860s, Franciscus Donders conducted an experiment to measure the time it takes to make decisions, specifically examining reaction times in tasks with different levels of complexity (simple vs. choice reaction time). His rationale was to infer the time it takes for mental operations (such as decision-making) by observing behavior (reaction times). He is credited with introducing the idea of measuring mental processes indirectly. Ebbinghaus’s Memory Experiments: Hermann Ebbinghaus conducted experiments on memory in the late 19th century, using nonsense syllables to test how quickly people could learn and forget material. He is famous for the forgetting curve, which shows how information is forgotten over time, and the learning curve, which describes how repeated practice leads to quicker learning. ○ Both Donders and Ebbinghaus measured mental processes through observable behavior, thus contributing to the development of cognitive psychology. Who founded the first laboratory of scientific psychology? Describe the method of analytic introspection that was used in this laboratory. ○ The first laboratory of scientific psychology was founded by Wilhelm Wundt in 1879 in Leipzig, Germany. Wundt’s laboratory is considered the birthplace of experimental psychology. Wundt used analytic introspection, a method in which trained participants would carefully describe their conscious experiences in response to stimuli, breaking them down into basic elements. This method aimed to identify the basic components of thought and perception, although it later became criticized for being subjective and unreliable. What method did William James use to study the mind? ○ William James studied the mind using introspection and functionalism. He focused on understanding the functions of the mind (how mental processes help us adapt to our environment) rather than analyzing its structure, as Wundt did. James believed that consciousness was a continuous flow and studied it in a more holistic way, focusing on its practical applications in everyday life. Describe the rise of behaviorism, especially the influence of Watson and Skinner. How did behaviorism affect research on the mind? ○ Behaviorism rose in the early 20th century, with figures like John B. Watson and B.F. Skinner leading the charge. Watson argued that psychology should focus solely on observable behavior, dismissing the study of the mind because it was too subjective. Skinner further developed this approach with his work on operant conditioning, emphasizing how behaviors are shaped by reinforcement and punishment. Behaviorism largely ignored mental processes, focusing instead on the relationship between stimuli and responses, and this led to a neglect of cognitive phenomena in research for several decades. How did Edward Tolman deviate from strict behaviorism? ○ Edward Tolman was a behaviorist but deviated from strict behaviorism by introducing the concept of cognitive maps. He argued that animals and humans develop mental representations of their environment (cognitive maps) and that these maps influence behavior. This idea acknowledged internal mental processes, which went against the strict behaviorist focus on external behaviors alone. What did Noam Chomsky say about Skinner’s book Verbal Behavior, and what effect did that have on behaviorism? ○ Noam Chomsky critiqued B.F. Skinner’s book Verbal Behavior, arguing that Skinner’s behaviorist framework could not explain the complexities of language acquisition. Chomsky pointed out that children produce novel sentences they have never heard before, suggesting that language development is not just a learned behavior based on reinforcement, as Skinner suggested. Chomsky’s critique was influential in challenging behaviorism and contributing to the rise of cognitive psychology. What is a scientific revolution, according to Thomas Kuhn? How is the cognitive revolution similar to the revolution that occurred in physics at the beginning of the 20th century? ○ According to Thomas Kuhn, a scientific revolution occurs when a paradigm shift takes place in a scientific field, where a new theory replaces the old, and researchers begin to view phenomena in a completely different way. The cognitive revolution in psychology was similar to the revolution in physics at the beginning of the 20th century (e.g., the shift from Newtonian physics to quantum mechanics) because both represented a shift away from existing theories (behaviorism in psychology, classical mechanics in physics) to new models that better explained the phenomena (cognitive processes in psychology, quantum phenomena in physics). Describe the events that led to the “cognitive revolution.” Be sure you understand the role of digital computers and the information-processing approach in moving psychology toward the study of the mind. ○ The cognitive revolution in psychology emerged in the 1950s and 1960s, spurred by several key events: Criticism of Behaviorism: Behaviorism’s neglect of mental processes and its inability to explain certain phenomena (like language acquisition) led to a call for a new approach. Digital Computers: The development of digital computers provided an analogy for understanding the mind. Computers process information, and researchers began to view the mind as an information-processing system. This shift in perspective, known as the information-processing approach, likened the mind to a computer that receives, processes, and outputs information. Chomsky’s Critique of Skinner: Chomsky’s critique of Skinner’s behaviorism and his emphasis on internal mental structures (like grammar) further pushed psychology toward a focus on cognition. What was the state of cognitive psychology in 1967, according to Neisser’s (1967) book? ○ In 1967, Ulric Neisser’s book Cognitive Psychology provided a comprehensive summary of the newly emerging field. At that time, cognitive psychology had become well-established as a distinct discipline, with growing interest in studying mental processes such as memory, perception, and problem-solving. However, the field was still developing, and many of its foundational theories and methodologies were in their infancy. What are neuropsychology, electrophysiology, and brain imaging? ○ Neuropsychology is the study of the relationship between brain function and behavior, particularly how brain injuries or abnormalities affect cognitive abilities. ○ Electrophysiology is the study of electrical activity in the brain, using techniques like EEG to measure brain waves and understand brain function during cognitive tasks. ○ Brain Imaging refers to techniques like fMRI and PET scans that allow researchers to visualize brain activity and structure, helping link cognitive processes to specific areas of the brain. What new perspectives on behavior emerged as cognitive psychology developed? ○ As cognitive psychology developed, behavior was increasingly understood in terms of internal mental processes. Researchers began to focus on how the mind processes information, solves problems, stores and retrieves memories, and makes decisions, shifting the focus from external behavior alone to a more holistic understanding of cognition. What are two suggestions for improving your ability to learn from this book? ○ Active Engagement: Actively engage with the material by taking notes, summarizing key concepts in your own words, and discussing the material with others. ○ Practice and Application: Apply the concepts you learn to real-world situations or hypothetical scenarios to better understand their practical relevance and to reinforce your learning. Review What is Cognitive Psychology? ○ The study of mental processes such as attention, memory, perception, problem-solving, language, and decision-making. ○ Focuses on understanding the internal processes that occur in the mind, how the mind works, and how it influences behavior. Historical Foundations of Cognitive Psychology ○ Structuralism (Wilhelm Wundt): Focused on introspection to understand the structure of the mind. ○ Functionalism (William James): Emphasized the functions of the mind and how mental processes help individuals adapt to their environment. ○ Behaviorism (John Watson, B.F. Skinner): Rejected introspection and focused on observable behaviors, marking a shift away from mental processes. ○ Cognitive Revolution: A shift from behaviorism to an interest in studying the mind again, influenced by figures like Noam Chomsky and the rise of digital computers. William James’s Principles of Psychology ○ Emphasized attention as a selective process, where the mind focuses on certain stimuli while ignoring others. ○ “Attention is the taking possession by the mind, in clear and vivid form, of one out of what seem several simultaneously possible objects or trains of thought." ○ His work laid the foundation for modern cognitive psychology despite the rise of behaviorism. Behaviorism (John Watson and B.F. Skinner) ○ John Watson: Founded behaviorism, emphasizing observable behavior over introspection, with experiments like "Little Albert." ○ B.F. Skinner: Developed operant conditioning, where behavior is shaped by reinforcements (positive or negative). ○ Critique of Behaviorism: The rise of cognitive psychology emerged as behaviorism could not explain complex behaviors like language acquisition. Cognitive Revolution (1950s) ○ A response to the limitations of behaviorism and sparked by the development of the information-processing model of cognition, inspired by digital computers. ○ Noam Chomsky criticized Skinner's operant conditioning theory of language acquisition, arguing for an innate biological program. ○ Edward Tolman demonstrated cognitive maps through his maze experiments, suggesting that mental processes play a role in behavior. ○ The information-processing model compared the mind to a computer that processes information in stages: input → memory → output. Paradigm Shifts in Science (Thomas Kuhn) ○ Thomas Kuhn’s theory of scientific revolutions explains how shifts in dominant scientific paradigms, such as the cognitive revolution in psychology, transform fields. ○ Behaviorism to cognitive psychology is an example of such a paradigm shift. Digital Computers and Cognitive Psychology ○ 1950s: Digital computers inspired the information-processing model of cognition. ○ Colin Cherry’s auditory experiment and Donald Broadbent’s filter model demonstrated how attention works by filtering and processing information. ○ Artificial Intelligence (AI): The 1956 Dartmouth conference led to advancements in AI, sparking the use of computers as models for understanding human cognition. The Cognitive Revolution ○ Ulrich Neisser's 1967 book "Cognitive Psychology" marked the formal establishment of cognitive psychology as a distinct field. ○ Focused on vision and hearing, and briefly discussed higher mental processes like thinking and problem-solving, which were not well understood at the time Key Contributions to Cognitive Psychology: ○ Richard Atkinson & Richard Shiffrin: Proposed a model of memory with three stages: sensory memory, short-term memory, and long-term memory. ○ Endel Tulving: Differentiated between types of long-term memory: episodic, semantic, and procedural. ○ Neuropsychology & Electrophysiology: Early research methods studying the brain’s role in cognition. ○ Brain Imaging Techniques: fMRI revolutionized cognitive psychology, allowing researchers to directly observe brain activity during cognitive tasks. Modern Cognitive Psychology ○ Today, cognitive psychology involves the study of higher mental processes and physiological aspects of cognition. ○ Emphasizes understanding cognition in real-world contexts, moving beyond laboratory studies. ○ Highlights the importance of prior knowledge in shaping cognitive processes. Important People ○ William James: Contributions to attention and the mind's selective nature. ○ John Watson: Founder of behaviorism, emphasizing observable behavior over mental processes. ○ B.F. Skinner: Developed operant conditioning and emphasized reinforcement in shaping behavior. ○ Edward Tolman: Challenged behaviorism by demonstrating the concept of cognitive maps. ○ Noam Chomsky: Criticized behaviorism's explanation of language development, advocating for innate cognitive structures. ○ Ulrich Neisser: Helped define cognitive psychology as a field with his 1967 book. ○ Endel Tulving: Differentiated between types of long-term memory, advancing research in memory studies. ○ Herb Simon and Alan Newell: Developed early AI programs that mimicked human problem-solving. Key Models and Theories ○ Information-Processing Model: Views the mind as a computer processing information through stages. ○ Broadbent’s Filter Model: Demonstrates how attention filters and processes information. ○ Atkinson-Shiffrin Model of Memory: Describes memory as having three components: sensory, short-term, and long-term memory. ○ Tulving’s Model of Long-Term Memory: Breaks down long-term memory into episodic, semantic, and procedural types. Important Experiments ○ Little Albert Experiment (Watson): Demonstrated classical conditioning. ○ Tolman’s Maze Experiment: Introduced the concept of cognitive maps. ○ Cherry’s Auditory Experiment: Showed how attention works by focusing on one message and filtering out others. ○ Skinner’s Operant Conditioning (Bar Pressing Experiment): Demonstrated how behavior is shaped through reinforcement. Modern Trends in Cognitive Psychology ○ Focus on higher mental processes (thinking, problem-solving, language). ○ Physiological research: Brain imaging techniques like fMRI provide insight into the physical aspects of cognition. ○ Real-world applications: Modern research examines cognition in everyday life, such as how knowledge influences perception. Chapter 2 Learning Objectives What is cognitive neuroscience, and why is it necessary? ○ Cognitive neuroscience combines the study of cognition with the understanding of the brain's physiological processes. It is necessary because it provides insight into how mental functions like perception, memory, and language are rooted in the brain's structure and activity. By examining neural mechanisms, cognitive neuroscience bridges the gap between behavior and brain function, offering a deeper understanding of human experiences. How is information transmitted from one place to another in the nervous system? ○ Information is transmitted via neurons, the basic units of the nervous system. Signals travel as electrical impulses called action potentials along the axon of a neuron. These impulses remain consistent in height and shape, ensuring effective long-distance communication. The frequency of neural firing corresponds to the intensity of sensory stimuli, and signals are passed to other neurons through synapses using chemical neurotransmitters. How are things in the environment, such as faces and places, represented in the brain? ○ Environmental stimuli are represented in the brain through neural firing. Specific neurons respond to particular features or objects (e.g., feature detectors in the visual cortex respond to orientation or movement). Representation involves three types of coding: ○ Specificity coding: A single neuron represents a specific stimulus (rare). ○ Population coding: A pattern of firing across many neurons represents stimuli. ○ Sparse coding: A small group of neurons fires in specific patterns to represent objects. ○ For example, the fusiform face area (FFA) specializes in recognizing faces, while the parahippocampal place area (PPA) responds to places. Brain imaging and studies have confirmed the localization of these functions. What are neural networks, and what is their role in cognition? ○ Neural networks are interconnected groups of neurons that communicate to process and transmit information across the brain. They support distributed representation, meaning multiple brain areas work together to carry out cognitive functions like vision, memory, and language. These networks form the basis for hierarchical processing, where simple inputs from lower brain regions combine to create complex representations in higher areas. Neural networks allow for integration and specialization, enabling the brain to handle the complexity of cognitive tasks. Test Yourself 1. Describe the idea of levels of analysis. ○ The levels of analysis framework examines a topic from multiple perspectives to develop a more comprehensive understanding. For cognition, this might involve behavioral observation, physiological processes, and neural mechanisms. For example, in analyzing memory, one could study behaviors associated with memory retrieval, investigate the brain's biochemical and electrical activity, and examine the specific neurons and circuits involved. 2. How did early brain researchers describe the brain in terms of a nerve net? How does the idea of individual neurons differ from the idea of a nerve net? ○ Early researchers, due to the limitations of staining techniques, believed the brain consisted of a continuous "nerve net," in which signals could travel uninterrupted in any direction. This concept suggested the brain was a seamless network. In contrast, the discovery of individual neurons demonstrated that the brain is composed of discrete cells that communicate through synapses. This shift laid the groundwork for the neuron doctrine, which holds that neurons are the functional units of the nervous system. 3. Describe the research that led Cajal to propose the neuron doctrine. ○ Camillo Golgi's silver nitrate staining technique allowed scientists to view neurons individually under a microscope. Ramon y Cajal used this method to study newborn animal brains, revealing that neurons are not continuous but discrete entities. He demonstrated that neurons communicate at specialized junctions (synapses) and form specific pathways (neural circuits). This research refuted the nerve net theory and established the neuron doctrine, highlighting neurons as independent units essential for brain function. 4. Describe the structure of a neuron. Describe the synapse and neural circuits. ○ A neuron consists of: ○ Dendrites: Branch-like structures that receive signals from other neurons. ○ Cell body (soma): Contains the nucleus and integrates incoming signals. ○ Axon: A long fiber that transmits signals to other neurons. ○ Axon terminals: Specialized endings that release neurotransmitters to communicate with other neurons. ○ The synapse is the gap between the axon terminal of one neuron and the dendrite of another. Neurotransmitters cross this gap to transmit signals. Neural circuits are organized pathways of connected neurons, enabling specific functions like reflexes, sensory processing, and memory formation. 5. How are action potentials recorded from a neuron? What do these signals look like, and what is the relation between action potentials and stimulus intensity? ○ Action potentials are recorded using microelectrodes placed inside or near a neuron. These signals appear as spikes of electrical activity and remain consistent in height and shape as they travel along the axon. Stimulus intensity is represented by the firing rate of action potentials: stronger stimuli result in a higher frequency of firing, while weaker stimuli produce fewer spikes over the same period. 6. How has the question of how different perceptions can be represented by neurons been answered? ○ Research involving single-neuron recordings and sensory coding mechanisms has provided answers: ○ Feature detectors: Hubel and Wiesel discovered neurons in the visual cortex that respond to specific features, such as orientation or movement. ○ Hierarchical processing: Neurons in higher brain areas respond to more complex stimuli, such as faces, through the integration of simpler features. ○ Sensory coding theories: ○ Specificity coding: Suggests individual neurons represent specific stimuli (e.g., a "Steve Carell" neuron). ○ Population coding: Posits that stimuli are represented by patterns of activity across many neurons. ○ Sparse coding: Suggests that a small group of neurons responds to multiple stimuli with distinct patterns. 7. How is neural representation for memory different from neural representation for perception? How is it similar? ○ Similarities: Both rely on neural coding mechanisms, where specific patterns of activity represent information. In perception, these patterns arise from external stimuli, while in memory, they are triggered by stored information. ○ Differences: ○ Perception: Involves real-time sensory input, activating neural circuits directly related to the stimuli. ○ Memory: Involves the retrieval of stored representations, activating circuits that re-create the original experience without external input. ○ While perception involves dynamic, incoming signals, memory depends on the reconstruction of past neural patterns. What is localization of function? Describe how localization has been demonstrated by neuropsychology and recording from neurons. Be sure you understand the principle of double dissociations. ○ Localization of function is the principle that specific brain areas are responsible for particular cognitive functions. Neuropsychology has demonstrated this by studying individuals with brain damage. For example, Broca’s aphasia (speech production impairment) and Wernicke’s aphasia (language comprehension impairment) occur due to damage in specific brain areas, Broca’s and Wernicke’s areas, respectively. The principle of double dissociation strengthens these findings by comparing patients with damage in different brain areas, demonstrating that two functions are independently processed by separate mechanisms (e.g., recognizing faces vs. objects). Recording from neurons further supports localization. For instance, Doris Tsao’s study showed that 97% of neurons in a specific temporal lobe region responded only to faces. Describe the basic principles behind functional magnetic resonance imaging. ○ Functional magnetic resonance imaging (fMRI) measures brain activity by detecting changes in blood oxygenation levels. When neurons are active, they consume more oxygen, and blood flow increases to those areas. fMRI captures these changes in small cubic units called voxels, allowing researchers to map brain activity during various tasks. Describe brain-imaging evidence for localization of function. Describe experiments that involved looking at still pictures and that involved looking at movies. What does each type of experiment tell us about localization of function? ○ Brain imaging, particularly fMRI, has identified specialized brain areas. For example: ○ Still Pictures: Viewing faces activates the fusiform face area (FFA), perceiving places activates the parahippocampal place area (PPA), and observing body parts activates the extrastriate body area (EBA). This demonstrates localized responses to specific stimuli. ○ Movies: Huth et al. (2012) used movie clips to map functional specialization across the brain. Their research revealed that brain areas respond to a range of objects and actions, showing that functional specialization extends to more dynamic and complex stimuli. ○ These studies suggest that localization exists but works alongside distributed processes for more intricate cognitive tasks. What is distributed representation? How is distributed representation related to the multidimensional nature of experience? How is distributed processing illustrated by how the brain responds to looking at faces, remembering, and language? ○ Distributed representation refers to the activation of multiple brain regions during a single cognitive process. This concept aligns with the multidimensional nature of experiences, where different aspects (e.g., emotion, movement, recognition) engage distinct brain areas. ○ Looking at Faces: Different brain regions process various aspects, such as recognizing identity (FFA), interpreting emotion, and assessing attractiveness. ○ Remembering: Episodic and semantic memories activate distinct brain areas, highlighting distributed representation in memory processes. ○ Language: Beyond Broca’s and Wernicke’s areas, other regions and pathways contribute to sound processing, word comprehension, and sentence production, showing a networked approach to language. What is a neural network? ○ A neural network is a system of interconnected brain areas that communicate to perform specific cognitive functions. Key principles include: ○ Structural pathways form the brain's "information highways." ○ Functional pathways serve specialized tasks within these networks. ○ Neural networks are dynamic, adjusting activity based on cognitive demands. ○ Even at rest, some networks, such as the default mode network (DMN), remain active. What is structural connectivity? How is it measured? ○ Structural connectivity refers to the physical "wiring" of the brain, composed of axonal pathways connecting different regions. It is measured using techniques like track-weighted imaging (TWI), which maps water diffusion along nerve fibers to visualize connections. These maps form the "connectome," a unique representation of an individual’s brain structure. What is functional connectivity? How is it measured, and what are some networks determined using this technique? ○ Functional connectivity refers to the synchronization of activity between brain regions. It is measured using resting-state fMRI, which identifies correlations in neural activity when the brain is at rest. Researchers have identified several networks, including: ○ Vision network ○ Motor network ○ Attention network ○ Executive function network ○ Salience network ○ Default mode network (DMN) What does it mean to say that the operation of brain networks is dynamic? ○ Dynamic operation refers to the brain’s ability to rapidly switch between networks based on tasks or internal states. For example, seeing a cup of coffee activates visual, attention, and motor networks sequentially. These shifts reflect the brain's adaptability and the flexible interactions between networks. What is the default mode network? How is it different from other networks? ○ The default mode network (DMN) is active when the brain is at rest and not focused on external tasks. It supports functions like mind-wandering, personal reflection, and creativity. Unlike task-specific networks, the DMN’s activity decreases during goal-directed tasks but increases during introspective states. Describe the connection between advances in technology and research on the physiology of cognition. ○ Technological advancements have shaped research on brain function: ○ 1928: Single-neuron recording allowed researchers to study basic neural responses. ○ 1970s and 1990s: PET and fMRI enabled mapping of brain organization and activity. These tools shifted research from studying simple behaviors to exploring complex cognitive processes like memory and decision-making. The focus remains on linking physiological mechanisms to experiences, thoughts, and behaviors, bridging behavioral and physiological experiments for deeper insights. 1. Historical Shifts in the Study of the Mind The field of cognitive psychology has experienced significant changes throughout history, shaped by scientific breakthroughs and technological advancements. 1.1. The 1800s: Foundations of Mental Process Research Early pioneers like Franciscus Donders and Hermann Ebbinghaus: ○ Donders: Conducted reaction time experiments to measure how long it takes to make decisions. Key concept: Mental chronometry. ○ Ebbinghaus: Focused on memory and developed the forgetting curve, which describes the decline of memory retention over time. 1.2. Early 1900s: Behaviorism's Rise Led by John Watson and B.F. Skinner: ○ Emphasis on observable behavior, rejecting introspection as unscientific. ○ Watson: Advocated for a stimulus-response framework. ○ Skinner: Developed operant conditioning, studying how rewards and punishments influence behavior. Limitation: Ignored internal mental processes. 1.3. The 1950s–1960s: The Cognitive Revolution Shift back to studying the mind, inspired by: ○ Information-processing model: Compared the mind to a digital computer with inputs, processes, and outputs. ○ Advances in technology, such as tools to record neural activity (e.g., single neurons). Key milestones: ○ Introduction of artificial intelligence (AI) concepts by scientists like Alan Turing. ○ Publication of Neisser’s Cognitive Psychology textbook in 1967. 2. Levels of Analysis in Cognitive Psychology Cognitive phenomena are studied through multiple perspectives to gain a deeper understanding of the mind. 2.1. Behavioral Analysis Focuses on observable actions. Example: Studying memory recall accuracy or reaction times in response to stimuli. 2.2. Physiological Analysis Investigates internal processes, such as chemical and electrical activity in the brain. Example: Gil and Mary in the park: Perceiving their conversation involves: ○ Chemical changes in neurons and synapses. ○ Electrical signals transmitted within the brain. ○ Recalling the event later uses the same neural pathways. 3. Neurons and Neural Processes Neurons are the basic units of the brain and nervous system, responsible for transmitting and processing information. 3.1. Early Conceptions of Neurons 19th-century belief: Brain was thought to consist of a continuous nerve net. Breakthroughs: ○ Golgi’s staining method: Made individual neurons visible under a microscope. ○ Cajal’s findings: Revealed that neurons are discrete units connected at synapses, not continuous. This discovery introduced the neuron doctrine and earned him the Nobel Prize (1906). 3.2. Neural Signaling and Action Potentials Edgar Adrian (1920s) recorded the first electrical signals from single neurons. ○ Key findings: Action potentials: Electrical signals that maintain their size and shape but vary in rate of firing based on stimulus intensity. Example: A stronger stimulus (e.g., pressing harder on skin) → Increased nerve firing rate → Stronger sensation. 4. Neural Representation and Cognition Our experiences are built on neural representations formed by firing patterns in the brain. 4.1. Neural Firing and Feature Detectors 1960s: Researchers began recording responses of single neurons in the primary visual cortex. Hubel & Wiesel’s discoveries: ○ Certain neurons, called feature detectors, respond to specific visual features (e.g., edges, orientation, movement). ○ Experience-dependent plasticity: Example: Kittens exposed only to vertical lines had neurons specialized for detecting vertical patterns, highlighting how experience shapes the brain. 4.2. Sensory Coding Specificity Coding: Suggests individual neurons respond to specific stimuli (e.g., one neuron for a face). Unlikely due to the brain's complexity. Population Coding: Patterns of activity across large groups of neurons represent a stimulus. Sparse Coding: A smaller subset of neurons represents stimuli efficiently. ○ Example: Brain areas responding to images of Steve Carell suggest sparse coding for facial recognition. 5. Complex Stimuli, Brain Localization, and Distributed Representation 5.1. Neurons and Complex Stimuli Charles Gross (1970s): Discovered neurons in the temporal lobe that respond to complex objects (e.g., hands, faces). Hierarchical processing: Neural signals combine as they progress to higher brain regions, enabling complex object recognition. 5.2. Localization of Function Cognitive functions are associated with specific brain areas: ○ Broca’s area: Speech production. ○ Wernicke’s area: Language comprehension. ○ Occipital lobe: Vision. ○ Fusiform face area (FFA): Facial recognition. Neuropsychology and modern imaging (e.g., fMRI, PET) support localization. 5.3. Distributed Representation While specific functions are localized, tasks like face recognition involve multiple brain areas working together. ○ Example: Recognizing a face involves memory areas, emotional regions, and visual processing. 6. Research Methods in Cognitive Psychology 6.1. Correlational Methods Definition: Examines relationships between variables to make predictions. Example: A positive correlation exists between regular studying and higher test scores. Limitations: ○ Correlation does not imply causation. ○ Third variables may influence outcomes (e.g., time management skills affecting both studying and scores). 6.2. Experimental Methods Definition: Manipulates one variable to examine its effect on another. Example: ○ Hypothesis: Regular textbook reading improves exam scores more than cramming. ○ Experiment: Compare performance of students who read regularly versus crammed. 8. Key Takeaways and Applications Cognitive psychology bridges behavior and neural mechanisms, highlighting how complex phenomena emerge from basic neural processes. Experimental approaches are vital to advance understanding, but researchers must interpret correlational findings cautiously. Active, strategic study methods enhance long-term retention and critical thinking. WEEK 2 Learning Objectives 1. Why can two people experience different perceptions in response to the same stimulus? Two people can experience different perceptions in response to the same stimulus due to individual differences in their past experiences, expectations, knowledge, and cognitive processing. For example, Crystal on the beach perceives driftwood as an umbrella because of her prior knowledge and reasoning, which might differ from someone else’s interpretation based on their own experiences. This illustrates how perception is not simply a passive reflection of the external world but is influenced by the internal context of the observer. 2. How does perception depend on a person’s knowledge about characteristics of the environment? Perception heavily depends on a person’s knowledge and expectations about the environment. This is demonstrated by Crystal's ability to interpret the scene on the beach, where her knowledge and prior experiences influence how she recognizes the umbrella and coiled rope. In scenes with ambiguous or incomplete information, people use their knowledge of common environmental features or "regularities" (like vertical lines often indicating buildings) to guide their perception. Similarly, semantic regularities (e.g., knowing that a kitchen scene likely contains food-related objects) help shape how individuals perceive and interpret the world around them. 3. How does the brain become tuned to respond best to things that are likely to appear in the environment? The brain becomes tuned to respond best to things likely to appear in the environment through the process of experience-dependent plasticity and evolutionary selection. For example, neurons in the visual cortex are more sensitive to horizontal and vertical lines (oblique effect), as these orientations are common in natural and human-made environments. This tuning happens because individuals or species that can efficiently process commonly occurring stimuli are more likely to survive and thrive. Over time, this selective responsiveness becomes ingrained, allowing for more efficient perception. 4. What is the connection between perception and action? Perception and action are tightly interconnected and coordinate seamlessly in everyday activities. As Crystal runs on the beach, her perception of the environment influences her movement (action), such as reaching for her coffee after identifying the object. This link between perception and action allows individuals to interact meaningfully with their surroundings. Perception guides action by providing the necessary information about the environment (such as the location of objects), while action can influence perception by altering the perspective or viewpoint from which we perceive the world. Test Yourself 1. What does Crystal’s run down the beach illustrate about perception? List at least three different characteristics of perception. Why does the importance of perception extend beyond identifying objects? Crystal’s run illustrates several key aspects of perception: Perception is dynamic: Crystal’s initial perception of the object as driftwood changed as she got closer and gathered more information. Perception involves reasoning and problem-solving: She used additional clues to correctly identify the object (an umbrella, not driftwood). Perception is guided by past experiences: Her ability to recognize the coiled rope as one continuous strand is influenced by previous experiences with ropes. Perception extends beyond identifying objects because it is essential for interacting with our environment, making decisions, forming memories, and solving problems, all of which help us navigate and understand the world. 2. Give some examples, based on the “perceptual puzzle” demonstration and computer vision, to show that determining what is out there requires going beyond the pattern of light and dark on the receptors. In the perceptual puzzle demonstration, the task of identifying objects from patterns of light and dark involves additional reasoning. For example, distinguishing a shadow from a solid object involves understanding the broader context and interpreting the visual information correctly. Similarly, a computer-vision system cannot simply rely on light and dark patterns to identify objects but must also interpret shadows, occlusions, and context to distinguish one object from another accurately. 3. What does our description of computer-vision capabilities beginning in the 1950s say about how difficult it has been to design computer-vision systems? The slow and primitive progress in computer-vision systems from the 1950s onward highlights the complexity of designing systems capable of human-like perception. Initially, it was believed that such systems would be developed quickly, but it took decades to make any substantial advances. Even today, computer-vision systems still struggle with tasks that humans perform effortlessly, such as interpreting ambiguous images or understanding context. 4. Describe four reasons why it is difficult to design a perceiving machine. Ambiguity of visual information: The retinal image can be caused by multiple objects, making it difficult for machines to deduce the correct object. Hidden or blurred objects: Machines struggle with recognizing partially obscured or unclear objects, whereas humans can infer what is hidden based on context and prior knowledge. Viewpoint invariance: Humans can recognize objects from different angles, but computer-vision systems struggle with matching points across various views. Contextual understanding: Human perception can quickly integrate high-level information, like background knowledge, into recognizing complex scenes, something machines struggle to do. 5. What is bottom-up processing? Top-down processing? Describe how the following indicate that perception involves more than bottom-up processing: (a) multiple personalities of a blob (b) hearing individual words in a sentence. Bottom-up processing: This starts with the raw sensory input (e.g., light hitting the retina) and builds up to higher-level cognitive processes. Top-down processing: This involves using prior knowledge, context, and expectations to interpret sensory input. (a) Multiple personalities of a blob: The same visual stimulus (a blob) can be interpreted in different ways based on the context, demonstrating that perception is influenced by top-down processing. The blob might be seen as a shoe or a car depending on the surrounding information. (b) Hearing individual words in a sentence: In speech perception, people can segment words from a continuous stream of sound, aided by knowledge of language and context. This shows top-down processing, as the listener uses their understanding of language to break the stream of sounds into recognizable words. 6. Describe Saffran’s experiment, which showed that infants as young as 8 months are sensitive to transitional probabilities. Saffran’s experiment demonstrated that infants as young as 8 months old can detect transitional probabilities—the likelihood of one syllable following another in a sequence. Infants were shown to pay more attention to “part-word” stimuli (syllable pairs that do not belong to real words) rather than “whole-word” stimuli, indicating they could recognize patterns in the speech stream and distinguish between actual words and fragments of words. This experiment shows the early development of statistical learning and how infants use transitional probabilities to segment speech and make sense of language. 7. Helmholtz’s Theory of Unconscious Inference and the Likelihood Principle Helmholtz’s theory proposes that perception is influenced by unconscious inferences, where the brain quickly deduces the most likely cause of a retinal image based on prior experiences. The likelihood principle suggests that we perceive the object most likely to have caused the retinal pattern we are seeing, relying on past experiences to make these judgments. This process is unconscious and occurs rapidly, making our perception seem instantaneous even though it involves reasoning. 8. The Gestalt Approach to Perception and Principles of Organization The Gestalt approach, in contrast to structuralism, emphasizes that perception is more than just the sum of its parts. Gestalt psychologists argue that the whole is perceived differently than individual sensations combined. They proposed several principles of perceptual organization: Good Continuation: Overlapping objects are perceived as continuous. Pragnanz: Stimuli are perceived in their simplest form. Similarity: Similar items (in color, shape, or size) are grouped together. These principles are thought to be intrinsic to human perception and are built into our perceptual system, unlike Helmholtz’s theory, which emphasizes the role of experience. 9. Regularities of the Environment Regularities in the environment refer to the recurring patterns or features that are commonly found in the world, which help us interpret and respond to sensory information. There are two types: Physical Regularities: These are consistent physical features, such as the prevalence of vertical and horizontal orientations in human-made and natural environments, which make them easier to perceive. Semantic Regularities: These relate to the meaning of scenes, such as the typical activities associated with certain places (e.g., kitchens for cooking).A scene schema is a mental representation of what is typically found in a particular scene, helping to guide our perception of objects based on the context. 10. Bayesian Inference and Its Application Bayesian inference involves using prior probabilities (beliefs about the likelihood of an outcome) and likelihood (how well the available evidence supports the outcome) to make perceptual judgments. In the "coughing" example, Bayesian inference would explain how we start with a belief (prior probability) that coughing might indicate a cold and update that belief with evidence (such as the severity of the cough) to determine the most likely diagnosis. In terms of object perception, Bayesian inference helps with the inverse projection problem, where multiple objects can produce the same retinal image. By using prior knowledge (e.g., assuming a book is rectangular), perception is guided to resolve these ambiguities. 11. Comparison of the Four Approaches Helmholtz’s Unconscious Inference: Focuses on past experiences shaping perception through unconscious inference. Gestalt Laws of Organization: Emphasize innate perceptual principles, such as good continuation and simplicity, which help organize sensory information. Regularities in the Environment: Suggest that perception is influenced by physical and semantic patterns in the environment. Bayesian Inference: Combines prior probabilities with evidence to interpret ambiguous stimuli and resolve perceptual uncertainties. The Gestalt approach differs from the other three because it focuses more on bottom-up processing, where innate principles organize perception without relying on experience. Modern psychologists, however, suggest that some of these Gestalt principles might be shaped by experience, providing a balance between innate mechanisms and learned perceptual rules. 12. What is the oblique effect? Describe how this effect could be caused by evolution and by experience. The oblique effect refers to the phenomenon where people are more sensitive to horizontal and vertical orientations in the environment than to oblique (diagonal) orientations. This effect is believed to be caused by evolution because organisms with visual systems that respond more effectively to these common environmental features (like edges and structures of natural environments) would be more likely to survive and reproduce. Over time, natural selection may have favored individuals with visual systems that better process these orientations. Experience also plays a role, as demonstrated by experience-dependent plasticity, where neural responses can be shaped by environmental exposure. For example, individuals raised in environments where horizontal or vertical stimuli dominate show stronger neural responses to these orientations. 13. Describe the interaction between perceiving and taking action, giving a specific example from everyday perception. Perceiving and taking action are closely linked, as perception often guides action. For example, when you pick up a cup of coffee, you first perceive its location and size. Then, you adjust your hand position and strength to grasp it properly. The perception of the cup’s position and weight informs your actions—how you move your hand and the amount of force needed. This dynamic process involves continuous feedback from your actions, adjusting your perception and motor response to accurately complete the task. 14. Describe the Ungerleider and Mishkin experiment. How did they use the procedure of brain ablation to demonstrate what and where streams in the cortex? Ungerleider and Mishkin (1982) conducted an experiment where they presented monkeys with two tasks: object discrimination (identifying an object) and landmark discrimination (locating an object relative to a landmark). They used brain ablation (removing parts of the brain) to determine which areas were responsible for each task. When they removed the temporal lobe, the monkeys had difficulty with the object discrimination task, suggesting that this area is responsible for recognizing objects (the "what" stream). When they removed the parietal lobe, the monkeys struggled with the landmark task, indicating that the parietal lobe is responsible for determining the location of objects (the "where" stream). These two processing streams were later identified as the ventral (what) and dorsal (where) pathways, each playing a distinct role in perception. 15. Describe how Milner and Goodale’s testing of D.F. demonstrated pathways for matching orientation and for combining vision and action. Describe the perception pathway and the action pathway. How do these pathways correspond to Ungerleider and Mishkin what and where streams? Milner and Goodale (1995) tested D.F., a woman with brain damage to her temporal lobe, by asking her to rotate a card to match a slot’s orientation. D.F. had difficulty with this task, but when asked to mail the card through the slot, she was able to rotate it correctly. This led researchers to propose that there are two separate pathways in the brain: the perception pathway (temporal lobe), which is responsible for identifying objects (the "what" pathway), and the action pathway (parietal lobe), which is responsible for determining object location and coordinating movement (the "how" or "where" pathway). These pathways mirror the what and where streams identified by Ungerleider and Mishkin, with the perception pathway focused on object recognition and the action pathway guiding motor actions like reaching or grasping. 16. Describe how the perception and action pathways both play a role in an action such as picking up a cup of coffee. In the act of picking up a cup of coffee, the perception pathway first identifies the cup’s size, shape, and position. Once this information is processed, the action pathway comes into play, guiding the movement of the hand to the cup, adjusting for its weight and distance, and determining how to grasp the handle. The two pathways work together in a seamless interaction: perception informs the action, and action fine-tunes perception (e.g., adjusting grip strength based on the weight of the cup). This dynamic interplay ensures the successful execution of tasks involving interaction with the environment. 17. What are mirror neurons? What have some researchers proposed about how mirror neurons might link perception and action? Mirror neurons are neurons that fire both when an individual performs an action and when they observe someone else performing the same action. These neurons have been observed in monkeys and are believed to exist in humans as well. Researchers have proposed that mirror neurons play a role in understanding the actions of others, as they allow an observer to "mirror" the actions of another, thereby helping to interpret the intentions behind those actions. For example, observing someone pick up a cup might activate the same neural circuits as if the observer were performing the action themselves, which could aid in understanding the goal of the action (e.g., drinking vs. cleaning). 18. What is the connection among knowledge, inference, and prediction? The connection among knowledge, inference, and prediction lies in how we use what we know to make sense of the world and anticipate future events. Knowledge provides a base of information that guides inferences—mental conclusions drawn from available data or sensory input. Prediction extends this process, allowing us to anticipate future occurrences based on past experiences and knowledge. For example, when you predict the weight of an object, your knowledge of its size and previous experiences help you infer how heavy it might be. This predictive framework influences not only perception but also memory, attention, language, and decision-making. Notes 1. Introduction to Perception Perception refers to the process by which we interpret sensory input, such as visual or auditory stimuli, to understand our environment and engage in actions accordingly. This process involves reasoning, problem-solving, and interpretation. Example: Imagine Crystal going for a morning run on the beach. She initially mistakes an umbrella for driftwood, but as she gathers more information, her perception changes. This illustrates how perception works in real-time, involving continuous updates based on new sensory input. 2. Basic Characteristics of Perception Not Automatic: Perception is a process that involves reasoning, problem-solving, and interpretation, not just a passive reaction. Interconnected with Action: Perception and action are closely tied, as seen in Crystal's run and decision to grab coffee, which involve both perceptual information and action. Influenced by Past Experience: Crystal assumes a rope is continuous because of her past experiences with coiled ropes. 3. Human vs. Computer Perception Human Perception: Humans are adept at recognizing objects from various perspectives and under different conditions. They rely on both bottom-up and top-down processing (e.g., expectations, prior knowledge). Computer Vision: Computers, despite advancements, still struggle with tasks like object detection. Early goals, like those seen in sci-fi, are far from fully realized, with machines making errors such as misidentifying a teapot as a tennis ball. 4. Why Perception Is Difficult for Machines Ambiguity in Stimulus: Objects may appear differently due to changes in lighting or angle, creating challenges for machines (e.g., inverse projection problems). Hidden or Blurred Objects: Humans can infer the existence of obscured objects using context and prior knowledge. Computers lack this inferential ability. Viewpoint Variance: Humans can recognize objects from multiple angles, but computers often require complex calculations for viewpoint recognition. High-Level Scene Interpretation: Humans can understand the context in a scene, whereas computers struggle to recognize the difference between a plane in an air show and a commercial flight. 5. Perceptual Mechanisms Bottom-Up Processing: This is a stimulus-driven process that starts with sensory input. For example, light reaching the retina triggers signals that the brain interprets as visual information. Top-Down Processing: Knowledge and expectations influence perception. For example, seeing a loaf of bread in a kitchen involves top-down processing because of the expectation based on past experience. 6. Helmholtz’s Theory of Unconscious Inference Helmholtz proposed that our perception of objects is based on unconscious inferences drawn from past experiences. When the retinal image is ambiguous, our brain unconsciously fills in the gaps by assuming the most likely cause based on prior knowledge. 7. Gestalt Principles of Organization Gestalt psychology emphasizes that perception is more than the sum of individual sensory components. Several key principles guide this organization: Good Continuation: We tend to perceive continuous objects, like a line that continues behind another object. Pragnanz (Simplicity): We simplify complex visual stimuli into their most basic form. Similarity: Objects of similar color, shape, or size are perceived as belonging together. 8. Regularities in the Environment Physical Regularities: These are common features in our environment that help us process information efficiently, such as the oblique effect, where we are more sensitive to vertical and horizontal orientations than to oblique angles. Light-from-Above Assumption: We tend to assume that light comes from above, affecting how we perceive shading and depth. Contour Completion: We tend to perceive the continuation of an object, even when it is partially obscured. Semantic Regularities: Our perception is influenced by the function or meaning of objects in a scene (e.g., recognizing that a kitchen involves food preparation). Scene Schemas: Mental representations of typical elements in a scene help us anticipate what we should expect to see, such as objects in an office or a kitchen. 9. Bayesian Inference Bayesian Inference combines prior knowledge and new evidence to resolve perceptual ambiguity: Prior Probability: Our initial beliefs or expectations about an outcome. Likelihood: The probability of an outcome, given new evidence. Example: When looking at an ambiguous shape, prior knowledge of typical object shapes guides our perception toward the most probable interpretation. 10. Multiple View Theory Evidence: This theory suggests that object recognition is based on multiple stored views of an object from different angles. Tarr & Gauthier (1998): Participants learned to recognize objects from different viewpoints. The study’s results suggest that these multiple views are stored separately, meaning we recognize objects based on a set of learned viewpoints. 11. Change Blindness Definition: Change blindness refers to the phenomenon where people fail to notice changes in a visual scene. Real-World Example: In the scenario of asking for directions on campus, when a door passes between two people, the question asker changes, but most people do not notice the switch. Why It Happens: Change blindness works because of a 250ms blank screen in the experiment, and attention is critical. Where we focus our attention influences what we perceive. 12. Neurons and Object Recognition Oblique Effect: Humans are more sensitive to vertical and horizontal orientations than to oblique angles. This preference is reflected in the distribution of neurons in the visual cortex. Neurons in the Visual Cortex: These neurons respond more to vertical and horizontal stimuli due to their prevalence in both natural and human-made environments. 13. Comparing Perceptual Theories Helmholtz’s Unconscious Inference: Emphasizes the role of past experience in perception. Gestalt Laws: Focus on innate principles of perceptual organization (e.g., continuity, similarity). Environmental Regularities: Perception is influenced by common patterns in the environment (e.g., light-from-above assumption). Bayesian Inference: Perception is updated by combining prior knowledge and new evidence, helping resolve ambiguities. 14. Summary Perception is an active process that involves complex interactions between sensory input, knowledge, and past experiences. Unlike machines, humans can use context, regularities, and expectations to guide their perceptions, making it easier for us to recognize objects and interpret scenes accurately. Both bottom-up and top-down processing, as well as theories like Helmholtz’s Inference, Gestalt Psychology, Bayesian Inference, and environmental regularities, contribute to our ability to navigate and understand the world around us. WEEK 3 Chapter 4 Learning Objectives Is it possible to focus attention on just one thing, even when there are many other things going on at the same time? Yes, it is possible to focus attention on just one thing, even in the presence of other distractions. This ability is linked to selective attention, where individuals actively choose which stimuli to focus on while ignoring others. Research on selective attention shows that people can prioritize specific stimuli based on relevance or importance, and use mechanisms like filtering to block out distractions. Focused attention allows people to concentrate on one task, like reading or having a conversation, even when other stimuli (like background noise) are present. This ability is limited, though, and can be overwhelmed by too many distractions. Under what conditions can we pay attention to more than one thing at a time? Paying attention to more than one thing at a time, known as divided attention, is possible under certain conditions, but it is limited. People can divide their attention when the tasks are low in cognitive demand or automatic. For example, you can walk and talk at the same time without much difficulty because walking is an automatic behavior. However, when tasks require more cognitive resources or concentration, it becomes difficult to divide attention effectively. Practice and familiarity with tasks can improve the ability to multitask, but there are always limits to how well we can manage multiple demanding tasks simultaneously. Task similarity also plays a role; if two tasks are similar, it is harder to divide attention successfully. What does attention research tell us about the effect of talking on cell phones while driving a car? Attention research shows that talking on a cell phone while driving can significantly impair driving performance. This is due to inattentional blindness, where the cognitive load of conversation diverts attention from the driving environment. Drivers on the phone may fail to notice important visual cues, such as changes in traffic or pedestrians, leading to slower reaction times and an increased likelihood of accidents. Even though hands-free devices might mitigate physical distractions, the cognitive load involved in maintaining a conversation competes with the mental resources needed for safe driving. Studies indicate that the brain's resources for attention are limited, and engaging in two tasks that both require cognitive effort can reduce performance in both tasks. Is it true that we are not paying attention to a large fraction of the things happening in our environment? Yes, it is true that we are not paying attention to a large fraction of the things happening in our environment. This is a concept known as inattentional blindness, where individuals fail to notice things in their environment that are outside their focus of attention. Our cognitive resources are limited, and we can only actively attend to a small fraction of the stimuli around us. This is why we might miss unexpected events, like a person in a gorilla suit walking across a basketball game, even though it’s clearly visible. Much of our environment remains unnoticed because our attention is selectively directed based on what we deem important or relevant, while the rest fades into the background. Test yourself Selective Attention, Distraction, Divided Attention, Attentional Capture, and Scanning: 1. Selective Attention: Roger focusing on his math homework despite nearby conversations in the library illustrates selective attention, where he concentrates on one stimulus while ignoring others. 2. Distraction: Roger’s focus shifts when distracted by the conversation while playing a game, demonstrating how external stimuli can disrupt attention. 3. Divided Attention: Roger dividing his attention between the game and the conversation showcases divided attention, where people attempt to focus on two or more tasks simultaneously. 4. Attentional Capture: The loud noise from the fallen book cart captures Roger’s attention, demonstrating how certain stimuli can instantly draw attention away from the current task. 5. Scanning: After the noise, Roger visually scans the commotion, highlighting how scanning refers to looking or searching for specific information or events. Dichotic Listening Procedure and Unattended Message: The dichotic listening procedure involves participants hearing different messages in each ear and being asked to shadow (repeat) the message in the attended ear. This method showed that participants could focus on the attended message and were largely unaware of the unattended message's content, though they could detect physical attributes like pitch or tone. However, they could not recall the message's meaning unless it contained important information (e.g., their name). The cocktail party effect refers to the phenomenon where, even in a noisy environment, people can suddenly detect meaningful stimuli, such as hearing their name mentioned in an unattended conversation. This effect demonstrates that some unattended information is processed to a degree that allows meaningful recognition. Broadbent’s Model of Selective Attention: Broadbent’s filter model suggests that information is processed in stages. First, sensory memory briefly holds all incoming stimuli. Then, a filter selects information based on physical characteristics (e.g., tone, pitch), allowing only the attended message to pass through for further processing. The attended message is then sent to the detector for deeper processing and to short-term memory. Broadbent’s model is called an early selection model because it suggests that the filtering occurs early, before the meaning of the information is processed, meaning unattended information is essentially ignored. Moray and Gray & Wedderburn’s Experiments: Moray’s experiment showed that participants could recognize their name in the unattended ear, suggesting that some unattended information is processed for meaning. Gray and Wedderburn’s study revealed that participants could integrate meaningful content from both ears, such as hearing “Dear Aunt Jane” when words were switched between ears. These results are difficult to explain with Broadbent’s model because they indicate that unattended messages are not entirely filtered out early but may be processed at some level. Treisman’s Attenuation Model: Treisman proposed the attenuation model to address the limitations of Broadbent's filter model. She suggested that the filter doesn't block unattended messages entirely but weakens them based on characteristics like meaning. Important stimuli, such as one’s name, have lower thresholds for detection, making them more likely to be noticed even when unattended. This modification explains how some unattended information can still be processed for meaning. MacKay’s “Bank” Experiment and Late Selection: MacKay’s experiment involved presenting ambiguous sentences (e.g., “They were throwing stones at the bank”) along with biasing words (e.g., “river” or “money”) in the unattended ear. The results showed that participants’ judgments about the sentences were influenced by the unattended words, implying that the meaning of these words was processed, even though they were unattended. This provides evidence for late selection, where most information is processed for meaning before selection occurs, contrary to early selection models. Forster and Lavie’s Experiment and Load Theory of Attention: Forster and Lavie’s experiment showed that distraction slowed response times more in easy tasks with low perceptual load compared to difficult tasks with high perceptual load. Their findings support the load theory of attention, which suggests that the ability to ignore distractions depends on the task’s perceptual load. Easy tasks use less cognitive capacity, leaving room for distractions to interfere, while difficult tasks require more cognitive resources, reducing the impact of distractions. Stroop Effect and Task-Irrelevant Stimuli: The Stroop effect involves the interference of automatic processes (like reading words) when they conflict with the task at hand (e.g., naming the color of the ink in which a word is printed). It illustrates how task-irrelevant stimuli, such as the word itself in the Stroop task, can interfere with attention and slow processing. The Stroop effect demonstrates the powerful role of automatic processing in attention and how difficult it can be to suppress irrelevant information. Central Vision vs Peripheral Vision: Central vision is the sharp, detailed vision that occurs when we focus directly on an object, facilitated by the fovea. Peripheral vision captures the broader scene around our focus, but with less detail. This difference relates to overt attention, where the eye moves to fixate on specific objects, enabling us to direct central vision towards things of interest. Fixations occur when our eyes pause on specific objects, while eye movements (saccades) allow us to shift attention to other areas, often influenced by both bottom-up (salient features) and top-down (goals and knowledge) factors. Stimulus Salience: Stimulus salience refers to the physical characteristics of a stimulus that make it stand out, such as color, contrast, or movement. It is a bottom-up factor, automatically drawing attention. For example, a bright object or an unexpected movement in our environment may capture our focus. The saliency of a stimulus influences how and where we direct attention during scene scanning. Cognitive Factors in Attention: Cognitive factors that affect attention include scene schemas, which are mental representations of what we expect to find in a specific context (e.g., a kitchen having a refrigerator, stove, etc.). If something out of place occurs, like a printer in the kitchen, it will attract attention because it violates the schema. Other cognitive factors, like goals and prior knowledge, also guide attention by making certain aspects of a scene more relevant to the task at hand. Peanut Butter Experiment: The peanut butter experiment demonstrated that attention is guided by task demands. Participants focus on the items needed for a task at the right moment, like looking at the peanut butter just before spreading it on bread. This "just in time" strategy illustrates how attention is directed by the cognitive demands of the task. Covert Attention and the Posner Procedure: Covert attention refers to shifting focus without moving the eyes. In Posner's precueing procedure, an arrow cues participants to focus on a location where a target will appear. The result showed that participants responded faster when attention was correctly directed, supporting the idea that attention enhances processing at the attended location, much like a spotlight or zoom lens. Egly's Precueing Experiment and Same-Object Advantage: In Egly's (1994) experiment, participants were asked to attend to a specific location on a rectangle. The same-object advantage was demonstrated when participants responded faster to targets that appeared at locations within the same object, even if they were farther from the cue, showing that attention to one part of an object spreads to other parts. Three Behaviorally Measured Outcomes of Attention: The three behaviorally measured outcomes of attention include: 1. Response time: How quickly a person responds to a target. 2. Accuracy: How correctly a person identifies or interacts with a target. 3. Eye movements: The pattern and direction of eye fixations. Data and DeYoe’s Study on Attention and Brain Activity: Data and DeYoe (2009) found that when participants attended to a specific location without moving their eyes, activity increased in specific areas of the brain related to that location. This shows that attention can influence neural processing in precise regions corresponding to the location or object of focus. Cukur’s Experiment on Attention and Object Representation: In Cukur's (2013) experiment, attention to specific object categories (e.g., "humans" or "vehicles") influenced brain activity in areas specialized for those categories. This attentional warping showed how attention not only enhances responses to the target but also affects the way the brain represents related categories, even across different cortical regions. Schneider and Shiffrin’s Experiment on Automatic Processing: In their 1977 experiment, Schneider and Shiffrin demonstrated automatic processing by having participants monitor distractor stimuli while holding target stimuli in memory. Initially, performance was poor, but after many trials, participants were able to perform the task with minimal cognitive resources, indicating that the task had become automatic with practice. Real-life examples of automatic processing include actions like locking a door, driving, or typing. Automatic processing becomes difficult when tasks are more complex, such as driving in heavy traffic or when targets and distractors are similar. Cell Phone Use and Driving: Experiments like the 100-Car Naturalistic Driving Study found that driver inattention, including cell phone use, is linked to many crashes and near-crashes, such as missing red lights or delayed braking. Despite this, many people, especially younger drivers, believe they can multitask while driving. This suggests that dividing attention between tasks (like driving and texting) can impair performance and increase risks, particularly in more demanding driving situations. Cell Phones and Other Areas of Performance: Cell phones also affect performance in contexts like studying. Studies show that 92% of college students use their phones during class, often distracting themselves with texting and browsing the internet, which impairs focus and academic performance. This is exacerbated by intermittent rewards, which reinforce the frequent checking of phones. Operant Conditioning and Cell Phone Checking: The principle of operant conditioning explains frequent cell phone checking through intermittent reinforcement. When people receive occasional rewards (like texts or notifications) for checking their phones, this reinforces the behavior, making them more likely to check again, even at the expense of focus on other tasks. Mind Wandering: Mind wandering occurs when attention drifts away from the current task, often toward unrelated thoughts. It is associated with the default mode network (DMN) in the brain. While mind wandering can reduce task performance, it can also enhance creativity and help with future planning. Evidence for Attention's Role in Perception: Several experiments highlight that attention is necessary for perception: Inattentional Blindness: People fail to notice visible stimuli if they aren't attending to them, like in the "basketball-passing" experiment where observers focusing on counting passes missed a person in a gorilla suit. Change Detection: Change blindness shows that people fail to notice changes in scenes if their attention isn't directed at the change. Inattentional Deafness: This occurs when focusing on one task, like a hard visual search, impairs the ability to detect other stimuli, such as sounds. Inattentional Deafness: Inattentional deafness refers to the failure to notice sounds due to focusing on a challenging task. The 2015 experiment by Raveh and Lavie showed that participants were less likely to detect a tone during a hard visual task, supporting load theory, which suggests that high cognitive load increases the likelihood of missing other stimuli. Awareness of Surroundings: We don't need to be aware of all the details in our environment because our perceptual system is adapted to focus on what is most relevant or important for survival. The system prioritizes stimuli that signal potential threats or critical information. Binding and the Binding Problem: Binding is the process by which different features (e.g., color, shape) of an object are combined to form a unified perception. The binding problem refers to the challenge of how the brain combines these features. Attention plays a key role in resolving this problem. Feature Integration Theory: Treisman's feature integration theory suggests that object processing occurs in two stages. The first is the preattentive stage, where features are analyzed separately. The second is the focused attention stage, where these features are combined to form a coherent object. Attention becomes involved in the second stage to integrate features. Illusory Conjunctions and Feature Analysis: Illusory conjunctions are when features from different objects are mistakenly combined. They demonstrate that attention is necessary for feature integration, as seen in experiments where participants reported seeing features of one object combined with another. Balint's syndrome patients, who have difficulty focusing attention, often experience more illusory conjunctions, supporting the theory. Feature Search vs. Conjunction Search: A feature search involves locating a target based on a single feature (e.g., color), while a conjunction search requires combining multiple features (e.g., color and shape). Balint’s patient struggled with conjunction searches but performed well with feature searches, highlighting the importance of attention in binding features. Attentional Networks: Attention is controlled by three main networks in the brain: Dorsal Attention Network: Governs top-down, voluntary attention control. Ventral Attention Network: Manages stimulus-driven, bottom-up attention. Executive Attention Network: Handles higher-order cognitive functions like decision-making and cognitive control. Effective connectivity and synchronization between these networks enhance attention, enabling us to focus on relevant stimuli and filter out distractions. Notes: Introduction The chapter begins by following Roger, a student in a library, as he navigates different aspects of attention. Initially, he focuses on math homework despite nearby conversations, demonstrating selective attention. Later, while playing a game, he becomes distracted by the same conversation, illustrating distraction. As he divides his attention between the game and conversation, we see divided attention in action. A loud noise from a fallen book cart draws his attention, followed by visual scanning of the event, exemplifying the complexity of attention. This chapter explores the history and mechanisms behind attention in cognitive psychology, incorporating both automatic and controlled attention processes. Broadbent’s Filter Model of Attention Broadbent’s filter model of attention, inspired by Colin Cherry’s dichotic listening experiments, explains how we focus on one auditory message while filtering out others. In dichotic listening, participants hear different messages in each ear and are asked to shadow the attended message. Cherry found that while basic features of the unattended message could be identified, its content was not remembered, demonstrating the cocktail party effect. Broadbent proposed that sensory memory briefly holds all incoming information, which is then filtered based on physical characteristics, allowing only the attended message to pass to the detector for further processing. Modifying Broadbent’s Model: More Early Selection Models Moray’s (1959) experiments showed that people could recognize their names in the unattended ear, challenging Broadbent's model and indicating that some unattended information is processed. Treisman (1964) introduced the attenuation model, where unattended messages are weakened but still processed. This "leaky filter" model emphasizes that selective attention involves both early and nuanced processing, with words like names having low thresholds, making them more likely to be noticed. A Late Selection Model Later selection models proposed that most information is processed for meaning before selection. Donald MacKay’s (1973) experiment demonstrated that participants were influenced by words presented in the unattended ear (e.g., "river" or "money" in a sentence like “They were throwing stones at the bank”), suggesting that meaning is processed even when the information is unattended. This model highlights how selection can occur later, after processing for meaning, as supported by Deutsch & Deutsch (1963) and Norman (1968). Processing Capacity and Perceptual Load Nilli Lavie (2010) introduced processing capacity (the amount of information we can handle) and perceptual load (task difficulty) as key factors in selective attention. In easy tasks, distractions are processed more, while in difficult tasks, distractions are less likely to be processed. Lavie’s theory is supported by Forster and Lavie’s (2008) findings, showing that distractions slow response times more in easier tasks than in difficult ones. Directing Attention by Scanning a Scene William James described attention as a process of "withdrawing from some things in order to effectively deal with others." We direct attention through eye movements, allowing us to focus on certain objects while ignoring others. Overt attention, such as saccadic eye movements, shows how we scan the environment to concentrate on specific stimuli. The ability to shift attention both overtly (through eye movements) and covertly (mentally shifting focus) allows us to filter information and focus on the most relevant stimuli in any given environment. Scanning a Scene with Eye Movements When identifying people in a photo, we scan each face individually. The eyes make rapid movements (saccades) between fixations, highlighting the roles of central and peripheral vision. The fovea, responsible for sharp vision, is key in these eye movements. Factors like bottom-up (stimulus-driven) and top-down (cognitive-driven) influences shape where and how we focus attention. The salience of stimuli, such as the color or contrast of an object, often determines how attention is directed in these processes. Scanning Based on Stimulus Salience Stimulus salience refers to the physical properties of an object, like color or contrast, that capture attention through bottom-up processes. For example, when searching for people with blonde hair, the task relies on the physical characteristics of hair color. As scanning continues, top-down processes, influenced by goals and prior knowledge, begin to guide attention to specific objects. This demonstrates how the brain prioritizes information based on both the immediate stimulus and broader contextual factors. Scanning Based on Cognitive Factors Top-down processes also play a key role in scene scanning. For instance, people tend to focus on objects that are unexpected, like a printer in a kitchen, based on scene schemas—mental representations of typical environments. These expectations guide where we direct attention, influenced by both cognitive factors and environmental knowledge. Cognitive factors also shape how automatic or controlled our attention is in certain situations. Scanning Based on Task Demands Attention is also guided by task demands. For example, when making a peanut butter sandwich, eye movements anticipate the next step, demonstrating the just-in-time strategy. People look at objects when they need them, influenced by both the task at hand and their knowledge of the environment. This highlights how controlled attention can be used to facilitate complex tasks by focusing on relevant details. Outcomes of Attention Attention allows us to focus more clearly on tasks or stimuli, enhancing perception. Covert attention (shifting attention mentally without eye movements) also impacts how we process objects and locations. The ability to shift attention efficiently and effectively is critical in managing daily activities and complex cognitive tasks. Attention Improves Our Ability to Respond to a Location In Posner et al.'s (1978) study on precuing, participants responded faster when attention was directed to a specific location, even when the cue was not visible. This suggests that attention acts like a spotlight, enhancing processing at the attended location. The study also demonstrated that moving attention is a controlled process that can be manipulated and influenced by external cues, further highlighting the interaction between automatic and controlled attention. Attention Improves Our Ability to Respond to Objects In Egly et al.'s (1994) experiment, participants responded quicker when the target appeared at a location on the same object, even if it was farther from the cue. This same-object advantage shows that attention spreads across the object, enhancing response times for related areas. This illustrates the concept of attention as both a focused and distributed process. Attention Affects Perception Attention not only speeds up responses but also alters perception. Attended objects appear more vivid, faster, and clearer than unattended ones, supporting James's claim that attention "takes possession by the mind." The way in which attention selectively enhances perception underlines the importance of this cognitive function in daily decision-making and information processing. Attention Affects Physiological Responding Brain activity increases in areas corresponding to attended locations or objects. fMRI studies by Datta and DeYoe (2009) and Cukur et al. (2013) show that attention enhances processing and affects brain responses to related categories, demonstrating how attention shapes neural activity. The brain’s ability to prioritize neural resources toward relevant stimuli reflects the critical role of attentional control in cognitive functioning. Divided Attention: Can We Attend to More Than One Thing at a Time? While multitasking is often challenging, divided attention is possible, especially for well-practiced tasks. For example, people can drive while having a conversation. However, distracting stimuli and task difficulty can make multitasking more difficult and dangerous. This relates to the concept of automaticity, where practice allows tasks to become more efficient and require less cognitive effort, allowing for divided attention. Divided Attention and Automatic Processing In Schneider and Shiffrin’s (1977) experiment, participants learned to divide attention between two tasks after extensive practice, illustrating the concept of automatic processing—tasks that become effortless and require little cognitive resources. This process is common in activities like driving or locking the door. However, as tasks become more complex, attention needs to be controlled, and automaticity may not be sufficient. Divided Attention Becomes More Difficult When Tasks Are Harder As tasks become more complex, dividing attention becomes harder. For instance, in challenging driving conditions, drivers must focus more on the task and may stop other activities, like talking or listening to music, to avoid accid

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