Cybernetics 2.0

Abstract

Norbert Wiener invented the word cybernetics and wrote a book by that name. The subject was feedback and control in the human body. The new book, “Cybernetics 2.0: a General Theory of Adaptivity and Homeostasis in the Brain and in the Body” follows in Wiener's footsteps. It is different as it introduces learning algorithms to Wiener's subject. Learning algorithms did not exist in Wiener's day. In the synapse, information is carried by neurotransmitter which in turn binds to neuroreceptors. The synapse is the coupling device from to neuron. The strength of the coupling, the “weight”, is proportional to the number of receptors. Their numbers can increase or decrease, as upregulation or downregulation. A mystery in neuroscience is, what is nature's algorithm for controlling upregulation and downregulation? Start with Hebbian learning and generalize it to cover downregulation as well as upregulation, and inhibitory as well as excitatory synapses. What results is a surprise ! We have an unsupervised form of the LMS(least mean square) algorithm of Widrow and Hoff. The Hebbian-LMS algorithm encompasses Hebb's learning rule (fire together, wire together), and introduces homeostasis into the equation. A neuron's “normal” firing rate is set by homeostasis. Physical evidence supports Hebbian-LMS as being nature's learning rule. LMS binds nature's learning to learning in artificial neural networks. The same Hebbian-LMS algorithm is key to the control of all the organs of the body, where hormones bind to hormonereceptors and there is upregulation and downregulation in the control process.