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Related Concept Videos

Cognitive Learning01:21

Cognitive Learning

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.
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Cognitivism01:17

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Cognitive psychology emerged as a significant field in the mid-20th century. It focused on understanding humans' internal mental processes. This approach emphasizes how people perceive, remember, think, and solve problems—elements critical to human cognition.
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Cognitive psychology is the field of psychology dedicated to examining how people think. It attempts to explain how and why we think the way we do by studying the interactions among human thinking, emotion, creativity, language, and problem-solving, as well as other cognitive processes. Cognitive psychology studies how information is processed and manipulated in remembering, thinking, and knowing.
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The cerebellum, while traditionally associated with motor control, also plays a crucial role in memory, particularly in procedural memory, which involves learning motor tasks that become automatic through repetition. For example, studies have shown that when the cerebellum is damaged, individuals or animals lose the ability to learn conditioned motor responses, such as the conditioned eye-blink response in classical conditioning experiments with rabbits. This study demonstrates the cerebellum's...
Neural Circuits01:25

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Hindbrain
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A Fully Automated Rodent Conditioning Protocol for Sensorimotor Integration and Cognitive Control Experiments
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Computational perspectives on forebrain microcircuits implicated in reinforcement learning, action selection, and

Daniel Bullock1, Can Ozan Tan, Yohan J John

  • 1Boston University, Department of Cognitive and Neural Systems, 677 Beacon Street, Boston, MA 02215, United States. danb@cns.bu.edu

Neural Networks : the Official Journal of the International Neural Network Society
|July 14, 2009
PubMed
Summary
This summary is machine-generated.

Computational neuroscientists are modeling forebrain microcircuits to understand flexible cognition and action. New models integrate basal ganglia functions for reinforcement learning and behavior, aiding neurological therapy predictions.

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Area of Science:

  • Neuroscience
  • Computational Neuroscience
  • Systems Neuroscience

Background:

  • Forebrain microcircuits are crucial for flexible cognition and action.
  • The basal ganglia play a key role in reinforcement learning and behavior control.
  • Understanding these circuits is vital for predicting neurological therapy outcomes.

Purpose of the Study:

  • To summarize recent computational models of forebrain microcircuits.
  • To explore the integration of basal ganglia functions in these models.
  • To connect microcircuit modeling with empirical discoveries for learning rules.

Main Methods:

  • Reviewing recent computational neuroscience models.
  • Analyzing the incorporation of realistic microcircuit features.
  • Synthesizing empirical findings on synaptic modification in cortico-striatal pathways.

Main Results:

  • Models increasingly incorporate realistic microcircuit representations.
  • Computational implications of these microcircuit features are being traced.
  • Emerging synthesis of hypotheses on cortical, basal ganglia, and thalamic interactions.

Conclusions:

  • Specialized microcircuits are hypothesized to solve brain learning and control problems.
  • Accurate microcircuit modeling is critical for neurological therapy development.
  • An integrated computational framework is developing for brain function.