"Connectionismadjective" Example Sentences
1. Connectionism models the brain as an interconnected network of nodes.
2. Connectionism theory suggests that learning occurs through strengthening connections between neurons.
3. The connectionist approach to language acquisition emphasizes the role of experience in shaping neural connections.
4. Connectionist models can simulate complex cognitive processes like language comprehension.
5. Connectionist networks are trained using backpropagation algorithms.
6. Connectionist models provide a valuable tool for studying neural plasticity.
7. The connectionist account of vision suggests that we recognize objects by activating patterns of neurons.
8. Connectionism emphasizes the importance of distributed processing in the brain.
9. Connectionist theories of cognition reject modular models of the mind.
10. Connectionism has been successfully applied to a variety of domains, including language, vision, and memory.
11. Connectionist models have been used to study the development of reading skills.
12. The connectionist approach to robotics emphasizes the role of learning in robot behavior.
13. Connectionist networks can be used to recognize patterns in data.
14. Connectionist models can help us understand how the brain processes information from sensory input.
15. Connectionism suggests that the brain is a dynamic system that continually adapts to its environment.
16. Connectionist theories of learning emphasize the importance of feedback in shaping neural connections.
17. Connectionist models can simulate the behavior of complex systems such as social networks.
18. Connectionism provides a framework for studying the relationship between brain and behavior.
19. Connectionist processes are thought to underlie many mental phenomena, such as attention and memory.
20. Connectionist models have been used to study the role of emotion in decision-making.
21. Connectionism is a useful tool for investigating the neural basis of language processing.
22. Connectionist networks can be used in machine learning applications.
23. Connectionist approaches to psychology have challenged traditional views of cognitive processes.
24. Connectionist models have been used to investigate the mechanisms underlying perceptual learning.
25. Connectionism provides insights into how the brain processes complex information such as language.
26. Connectionist models can help us understand the nature of mental disorders such as schizophrenia.
27. Connectionist theories emphasize the importance of context in shaping neural activity.
28. Connectionist models can be used to study the relationship between genes and behavior.
29. Connectionism suggests that the mind is not a static entity, but continually changes in response to experience.
30. Connectionist networks offer a powerful tool for studying complex systems and phenomena.
Common Phases
1. The connectionism-based model accurately predicted the behavior of the system;
2. The results of the study suggest that connectionist approaches may have significant implications for cognitive science;
3. The researchers used a connectionist framework to analyze the data and identify patterns;
4. Connectionist networks have been shown to be especially useful in identifying complex patterns in large datasets;
5. The use of connectionist models has revolutionized our understanding of how neural networks operate;
6. Connectionist approaches have been applied successfully in a wide range of domains, including natural language processing and visual object recognition;
7. Despite their potential, connectionist models still face certain limitations and challenges;
8. The connectionist paradigm emphasizes the importance of distributed representations and dynamic processing.