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Related Concept Videos

Cognitive Learning01:21

Cognitive Learning

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Cognitive learning is based on purposive behavior, incidental learning, and insight learning.
E. C. Tolman's theory of purposive behavior emphasizes that much behavior is goal-directed. He argued that to understand behavior, we must look at the entire sequence of actions leading to a goal. For instance, high school students study hard, not just due to past reinforcement but also to achieve the goal of getting into a good college.
Tolman introduced the idea that behavior is influenced by...
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Storage01:23

Storage

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A schema is a mental framework that helps individuals organize and interpret information. Schemata, formed from previous experiences, influence how we process new information: how we encode it, the inferences we make, and how we retrieve it. For instance, a schema for what a typical classroom looks like might include desks, a teacher's desk, a whiteboard, and students in such an environment. This expectation helps us quickly understand and navigate new classrooms without needing to analyze...
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Impact of Schemas01:30

Impact of Schemas

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Schemas are cognitive structures that provide a framework for interpreting and organizing social information. They help individuals navigate complex environments by offering expectations about people, events, and behaviors. Schemas influence attention, encoding, and retrieval processes, thereby shaping the entire trajectory of information processing in social contexts.Attention and Cognitive LoadDuring initial attention, schemas function as filters that prioritize schema-consistent information,...
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Observational Learning01:12

Observational Learning

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Albert Bandura's observational learning, also known as imitation or modeling, occurs when a person observes and imitates another's behavior. It is a quicker process than operant conditioning. A well-known example is the Bobo doll study, where children who saw an adult acting aggressively towards the doll were more likely to act aggressively when left alone, compared to those who observed a nonaggressive adult. Many psychologists view observational learning as a form of latent learning...
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Associative Learning01:27

Associative Learning

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Associative learning is a fundamental concept in behavioral psychology, wherein a connection is established between two stimuli or events, leading to a learned response. This process is critical in understanding how behaviors are acquired and modified. Conditioning, the mechanism through which associations are formed, can be divided into two main types: classical conditioning and operant conditioning, each elucidating different aspects of associative learning.
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Higher Mental Functions of Brain: Learning and Memory01:26

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Memory is one of the most vital higher mental functions of the brain. Memory is closely related to learning because it enables us to retain information and experiences from our past to use them in our present life. It also helps us to remember facts, events, and skills, such as riding a bike or swimming. There are two types of memory — declarative memory, which involves memorizing facts or events, and procedural memory, which enables us to remember how to do something like writing or...
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Clone-structured graph representations enable flexible learning and vicarious evaluation of cognitive maps.

Dileep George1, Rajeev V Rikhye2,3, Nishad Gothoskar2,4

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We introduce the clone-structured cognitive graph (CSCG), a novel framework for understanding how the hippocampus forms cognitive maps. This model explains how the brain generalizes information and plans flexibly by creating context-specific representations.

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Area of Science:

  • Neuroscience
  • Cognitive Science
  • Artificial Intelligence

Background:

  • Cognitive maps are essential for flexible behavior, requiring the hippocampus to manage complex spatial and conceptual relationships.
  • The hippocampus must generalize and plan efficiently by appropriately separating or merging observations across different contexts.

Purpose of the Study:

  • To propose a novel computational framework, the clone-structured cognitive graph (CSCG), to explain cognitive map formation.
  • To demonstrate how CSCGs address challenges in generalization and planning within hippocampal function.

Main Methods:

  • Developed a higher-order graph structure (CSCG) representing observations in different contexts as 'clones'.
  • Utilized a probabilistic sequence model for efficient CSCG learning, inherently robust to uncertainty.

Main Results:

  • CSCGs explain phenomena like discovering spatial relations from ambiguous data, transitive inference, and transferable schema formation.
  • The model accounts for splitter cells in navigation and event-specific responses, offering a unified explanation for place cell remapping.

Conclusions:

  • CSCGs provide a unifying framework for hippocampal function, revealing latent modularity for abstraction and planning.
  • This approach offers a potential pathway for developing relational abstraction capabilities in artificial intelligence.