Anastomotic Nets Combat mg Noise 285 



(January 6, 1962), E. G. Gray has published the first electron 

 microscopic anatomical evidence of axonal terminations upon 

 boutons of other axons, which may account, as proximally as 

 possible, for the interaction. 



Interaction of afferents is of great theoretical importance. First, 

 it enables a neuron to compute any Boolean function of its inputs, 

 i.e., to respond to a specified set of afTerent impulses, not merely 

 those functions available to so-called threshold logic; and, .second, 

 it permits a neuron to run tlirough all possible sequences of func- 

 tions as its threshold is shifted. 



The first is of great importance in audition. The Boolean func- 

 tion is an exclusive OR, and the important cells are in the superior 

 olive. Each cell will respond to an impulse from either ear unless 

 there is one from the other, but never to both or neither. The 

 utility of this arrangement is obvious to anyone with wax in one 

 ear. Put on a pair of earphones with a beep in one ear and drown 

 it 10 decibels under with noise. Next, put the same noise into the 

 other ear also, and the beep is as loud and clear as it is without 

 the noise. Finally, put that beep into the other ear also and it 

 disappears, for it is 10 decibels below the noise. Please note that 

 this noise is external to the central nervous system and is not the 

 kind that we shall consider later. 



The second, or sequence of functions determined by shifting 

 threshold, is of great importance in respiration but is not so easily 

 stated. As nearly as I can tell from old experiments and from the 

 literature, the rise in threshold to electrical stimulation that is due 

 to ether is approximately the same in all neurons; yet the respira- 

 tory mechanism continues to work under surgical anesthesia when 

 the threshold is raised, at least in cortex and cord, by approxi- 

 mately 200 per cent. The input-output function of the respiratory 

 mechanism remains reasonably constant, although the threshold 

 of its component neurons has changed so much that each is com- 

 puting a different function (or responding to a diflTerent set) of 

 the signals it receives. Von Neumann called such nets "logically 

 stable under a common shift of threshold," and Manuel Blum has 

 cleaned up the problem for appropriate nets of neurons with any 

 number of inputs. 



