BCS 153 Lecture Notes - Lecture 33: Flow Visualization, Artificial Neural Network, Connectionism

• School: University of Rochester
• Department: Brain and Cognitive Sciences
• Course: BCS 153
• Professor: Yang

Document Summary

Each hypothesized level of representation or processing can be represented in a diagram by a box, and the relationships between them by arrows . Visualization of a theoretical framework without complex equations. More detailed visualization of a cognitive event such as object recognition. Used for an attempt to simulate how brain works for a cognitive event: artificial. Neural network, activation(exhibition) vs. inhibition, specific notion of how a neuron is activated. Similarities and differences b/w box-and-arrows and connectionist model. They both have input processing and output generation. Both have bottom-up and top-down processes (both can be interactive) Memory is made up of neural networks that interact to store information. Memory is stored by modifying the strength of connections b/w neural units. Neurons that wire together = stronger connections b/w them, no interaction = memory strength weakens. Memory is stored in neural networks and is strengthened/weakened based on the connections b/w neurons. Used largely to simulate a decomposable phenomenon.