Cognitive Psychology Overview Quiz

A method for measuring the duration of mental processes by recording reaction times to different tasks.

A concept developed by Hermann Ebbinghaus, suggesting that memory retention decreases over time.

A school of thought that emphasizes the study of observable behavior, rejecting introspection as a method for understanding the mind.

A framework that posits that learning occurs through associations between stimuli and responses.

A type of learning where behaviors are modified based on their consequences, such as rewards or punishments.

A shift in psychological research that emphasized internal mental processes, drawing inspiration from the information-processing model and advances in technology.

A model that compares the mind to a computer, with inputs, processes, and outputs.

The study of cognitive phenomena from multiple perspectives, including behavioral, physiological, and computational approaches.

A smaller set of neurons can efficiently represent complex stimuli. For instance, brain areas activated by Steve Carell's face suggest sparse coding for facial recognition.

Brain regions process information in stages, building upon previous stages to create complex understanding. Signals combine as they move up the brain, allowing complex object recognition.

Specific areas of the brain are linked to specific cognitive functions. For example, Broca's area controls speech production, Wernicke's area handles language comprehension, and the occipital lobe processes vision.

A function like face recognition involves multiple brain areas working together. Recognizing a face involves memory, emotions, and visual processing.

Examines the relationships between variables to make predictions. For example, a positive correlation exists between regular studying and higher test scores.

Manipulates one variable to see its effect on another. For example, an experiment could test whether regular textbook reading improves exam scores more than cramming.

Cognitive psychology links behavior to brain mechanisms, explaining how complex thinking arises from basic neural operations.

Active study strategies like spaced repetition and practice testing improve long-term retention and critical thinking.

Perception is not just a passive reflection of the environment, but is actively shaped by a person's past experiences, expectations, knowledge, and how their brain processes information.

Our knowledge and experiences about the world influence how we perceive it. We tend to see things in ways that are consistent with our expectations and knowledge.

The brain is wired to respond efficiently to common elements in the environment. For example, we are more attuned to horizontal and vertical lines because these are frequently found in our surroundings.

Our brain adapts to our experiences, becoming better at recognizing patterns and information that is commonly encountered. This helps us interpret visual information effectively.

Perception and action work together seamlessly, guiding us through everyday activities. What we perceive influences how we act, and in turn, our actions can shape what we perceive.

Our brain often fills in missing information or makes assumptions based on what is likely to be present in a situation. This happens because we have learned to anticipate certain patterns in the world.

Our brains are capable of interpreting complex scenes by identifying common patterns and relationships between objects. This allows us to quickly understand and make sense of the world around us.

Experience plays a crucial role in shaping how we perceive the world. Our brain becomes more efficient at processing information that we frequently encounter, which helps us navigate and understand our surroundings.

The ability to perceive objects and situations accurately, involves reasoning, influenced by past experiences, and plays a crucial role in interacting with the world.

The process of changing our view or position to gain new information about an object or environment.

The demonstration highlights the need to go beyond simple light patterns to understand visual information, as shadows and context are crucial for accurate object identification.

Computer vision systems that are capable of interpreting shadows, occlusions, and context, going beyond just recognizing light patterns.

The early limitations in computer-vision development suggest that creating artificial systems that can replicate human perception is a complex and challenging feat.

An example of experience influencing perception, where the ability to see a coiled rope as one continuous strand is based on previous encounters with similar objects.

The process of using existing knowledge and reasoning to interpret visual information and accurately identify objects.

The initial perception of an object changes over time due to gathering more information, such as moving closer to an object or observing it from different angles.

The difficulty lies in the ambiguity of visual information. The same retinal image can be caused by multiple objects, making it challenging for machines to identify the correct object.

Computer-vision systems struggle with recognizing objects that are partially hidden or blurry. Humans, however, can infer what is hidden based on context and prior knowledge.

Humans can recognize objects from different viewpoints. Machines, however, struggle with matching points across various views, making it difficult for them to identify the same object from different angles.

Human perception incorporates high-level information, like background knowledge and context, to identify complex scenes. Machines struggle with this complex integration.

This starts with the raw sensory input (e.g., light hitting the retina) and builds up to higher-level cognitive processes.

This involves using prior knowledge, context, and expectations to interpret sensory input.

The same visual stimulus can be interpreted differently based on context, demonstrating that perception is influenced by top-down processing. For example, a blob might be seen as a shoe or a car depending on the surrounding information.

People can segment words from a continuous stream of sound, aided by knowledge of language and context, demonstrating top-down processing. The listener uses their understanding of language to break the stream of sounds into recognizable words.

We tend to assume light comes from above, which influences how we perceive shading and depth. For example, a shadow beneath an object makes it appear further away because we assume the light source is above.

We tend to perceive the continuation of an object even when it is partially obscured. Our brain 'fills in' the missing parts to complete the shape according to our expectations.

Our perception is influenced by the meaning or function of objects in a scene. We use our knowledge about the world to make sense of what we see. Imagine a banana in a kitchen vs a banana on a beach.

Mental representations of what is typical in a scene help us anticipate what we should expect to see. You might see a desk, computer, and chair in a typical office, but not a bathtub.

A method for resolving perception ambiguity, Bayesian inference combines prior beliefs and new evidence. It's like making a decision based on your existing knowledge combined with the information you just received.

We recognize objects by remembering multiple views of them from different angles, like storing a 3D model of the object.

This phenomenon occurs when people fail to notice changes in a visual scene, even when those changes are significant. It's like you blink and something's different, but you don't notice.

We are more sensitive to vertical and horizontal orientations than oblique angles. This is reflected in the organization of neurons in the visual cortex.