Class Notes CIS 675 Neural Networks CIS 675 Péter Molnár, 2001 (all rights reserved) Slide 1 Neural Networks How the brain works Neural Networks Mathematical Representation Structure of Neural Networks Examples: Boolean functions Perceptrons CIS 675 Péter Molnár, 2001 (all rights reserved) Slide 2 Neural Networks How the Brain Works Axonal arborization Axon from another cell Synapse Dendrite Axon Nucleus Synapses Cell body or Soma CIS 675 Péter Molnár, 2001 (all rights reserved) Slide 3 Neural Networks How the Brain Works (2) neuron: fundamental functional unit of all nervous system tissue, soma: cell body, contains cell nucleus Axonal arborization dendrites: a number of fibers, inputs Axon from another cell Synapse Dendrite Axon Nucleus Synapses Cell body or Soma CIS 675 Péter Molnár, 2001 (all rights reserved) axon: single long fiber, many branches, output synapse: junction of axon and dendrites, each neuron forms synapses with 10 to 100,000 other neurons. Slide 4 Neural Networks How the Brain Works (3) Signals are propagated from neuron to neuron be a electrochemical reaction: 1. chemical substances are released from the synapses and enter the dendrites, raising or lowering the electrical potential of the cell body; 2. when a the potential reaches a threshold, an electrical pulse or action potential is sent down the axon; 3. the pulse spreads out along the branches of the axon, eventually reaching synapes and releasing transmitters into the bodies of other cells; excitory synapses: increase potential, inhibitory synapses: decrease potential. CIS 675 Péter Molnár, 2001 (all rights reserved) Slide 5 Neural Networks How the Brain Works (4) Synaptic connections exhibit plasticity – long term changes in the strength of connections in response to the pattern of stimulation. Neuron also form new connections with other neurons, and sometimes entire collections of neurons migrate. These mechanisms are thought to form the basis of learning. CI

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