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Observational Learning01:12

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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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E. C. Tolman emphasized the purposiveness of behavior — the idea that much of our behavior is goal-directed. For instance, employees who aim for a promotion work diligently to meet their targets. Tolman argued that when classical conditioning and operant conditioning occur, the organism acquires certain expectations. In classical conditioning, a child might fear a dog because they expect it to bite. In operant conditioning, a person might consistently work overtime because they expect a...
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Cognitive learning is based on purposive behavior, incidental learning, and insight learning.
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Updated: Mar 13, 2026

Visualization Method for Proprioceptive Drift on a 2D Plane Using Support Vector Machine
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Neural network model develops border ownership representation through visually guided learning.

Akihiro Eguchi1, Simon M Stringer1

  • 1Oxford Centre for Theoretical Neuroscience and Artificial Intelligence, Department of Experimental Psychology, University of Oxford, Oxford, UK.

Neurobiology of Learning and Memory
|November 5, 2016
PubMed
Summary
This summary is machine-generated.

This study shows how top-down connections in the brain help develop visual border ownership representations. Computer simulations reveal these connections guide learning in early visual cortex (V1/V2).

Keywords:
Border ownershipNeural network modelPrimate vision

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Area of Science:

  • Neuroscience
  • Computational Neuroscience
  • Computer Vision

Background:

  • Visual perception assigns luminance contrast borders to image regions.
  • Neuronal coding of border-ownership exists in the primate visual system.
  • The developmental mechanisms of border-ownership are not fully understood.

Purpose of the Study:

  • Investigate the development of border-ownership representations through visually-guided learning.
  • Model the role of top-down connections in early visual cortex (V1/V2).
  • Explore how higher-level representations modulate lower-level visual processing.

Main Methods:

  • Computer simulation of a hierarchical neuronal network.
  • Utilized competitive neuronal layers with bottom-up and top-down connections.
  • Employed a biologically plausible temporal trace learning rule for synaptic self-organization.
  • Trained the network on diverse visual object shapes.

Main Results:

  • Demonstrated that top-down connections guide competitive learning in lower neural layers.
  • Showed the formation of border-ownership representations in V1/V2.
  • Confirmed modulation of V1/V2 representations by higher-level object boundary elements from V4.
  • Identified limitations in handling simultaneous multiple object presentations.

Conclusions:

  • Top-down connections are crucial for developing border-ownership representations in early visual cortex.
  • The model provides insights into the interplay between different hierarchical levels of visual processing.
  • Further research is needed to address complex visual scenes with multiple objects.