Neural network software simulates and predicts the behavior of biological or organic neural networks. It allows scientists to understand neural systems and conduct hypothetical situations that are unethical or impractical to replicate using live test subjects.
Neural network software is computer software used to simulate and predict the behavior of neural networks. Neural networks are complex networks of biological or organic signals, including systems within the body, such as the central nervous system, or patterns within the brain. This type of software can be used to model and make fairly accurate predictions about the development of a situation through user-generated input. Researchers and scientists typically use this type of software to help them understand neural systems in the absence of suitable test subjects, allowing them to make educated guesses about the possible outcomes of various situations in the laboratory.
A biological neural network is a network of neurons that communicate with each other to achieve a particular goal. For example, when an individual wants to move their hands, signals are generated in the body and sent along the central nervous system through nerve pathways in the body, moving from the brain to the spine and eventually wrapping around the hand, allowing the movement to take place. This process generates pulses of bioelectricity throughout the body, much like ripples moving across the surface of a disturbed pond, which carries the signals and spikes activity along the desired path of the neurons. Neural network software allows scientists to ‘see’ ongoing behavior through computer-aided simulation, measuring its impact on various other parts of the body.
The complexity of neurons and neural networks makes it impossible to manually model these kinds of situations. By allowing neural network software to calculate how bioelectrical signals move through the body, scientists can focus on the actual effect of the action, instead of getting bogged down in the process itself. This simplifies research, allowing scientists to conduct hypothetical “what if?” situations that it would be unethical or impractical to replicate using live test subjects.
For example, one could imagine a study investigating the damage caused by a stroke as it occurs. While it would be highly unethical to take a test subject and induce a stroke, the same effect can be produced by modeling the event in neural network software. This software creates a virtual “sandbox” where scientists can play with the effects of certain neural stimuli and see the damage they could cause to the body.
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