The term hybrid neural network can have two meanings: #

Biological neural networks A neural circuit is a population of neurons interconnected by synapses to carry out a specific function when activated. Neural circuits interconnect to one another to form large scale brain networks. Biological neural networks have inspired t ...

interacting with artificial neuronal models, and # Artificial neural networks with a symbolic part (or, conversely, symbolic computations with a

connectionist Connectionism refers to both an approach in the field of cognitive science that hopes to explain mental phenomena using artificial neural networks (ANN) and to a wide range of techniques and algorithms using ANNs in the context of artificial int ...

part). As for the first meaning, the

artificial neuron An artificial neuron is a mathematical function conceived as a model of biological neurons, a neural network. Artificial neurons are elementary units in an artificial neural network. The artificial neuron receives one or more inputs (representing ...

s and synapses in hybrid networks can be digital or

analog Analog or analogue may refer to: Computing and electronics * Analog signal, in which information is encoded in a continuous variable ** Analog device, an apparatus that operates on analog signals *** Analog electronics, circuits which use analog ...

. For the digital variant

voltage clamp The voltage clamp is an experimental method used by electrophysiologists to measure the ion currents through the membranes of excitable cells, such as neurons, while holding the membrane voltage at a set level. A basic voltage clamp will itera ...

s are used to monitor the membrane potential of

neuron A neuron, neurone, or nerve cell is an electrically excitable cell that communicates with other cells via specialized connections called synapses. The neuron is the main component of nervous tissue in all animals except sponges and placozoa. ...

s, to computationally simulate artificial neurons and synapses and to stimulate biological neurons by inducing synaptic. For the analog variant, specially designed electronic circuits connect to a network of living neurons through electrodes. As for the second meaning, incorporating elements of symbolic computation and artificial neural networks into one model was an attempt to combine the advantages of both paradigms while avoiding the shortcomings. Symbolic representations have advantages with respect to explicit, direct control, fast initial coding, dynamic variable binding and knowledge abstraction. Representations of artificial neural networks, on the other hand, show advantages for biological plausibility, learning,

robustness Robustness is the property of being strong and healthy in constitution. When it is transposed into a system, it refers to the ability of tolerating perturbations that might affect the system’s functional body. In the same line ''robustness'' ca ...

(fault-tolerant processing and graceful decay), and generalization to similar input. Since the early 1990s many attempts have been made to reconcile the two approaches.

References

Biological and artificial neurons

References

See also