The role of synapses in cortical computation

The synapse, first introduced as a physiological hypothesis by C. S. Sherrington at the close of the nineteenth century, has, 100 years on, become the nexus for anatomical and functional investigations of interneuronal communication. A number of hypotheses have been proposed that give local synaptic interactions specific roles in generating an algebra or logic for computations in the neocortex. Experimental work, however, has provided little support for such schemes. Instead, both structural and functional studies indicate that characteristically cortical functions, e.g., the identification of the motion or orientation of objects, involve computations that must be achieved with high accuracy through the collective action of hundreds or thousands of neurons connected in recurrent microcircuits. Some important principles that emerge from this collective action can effectively be captured by simple electronic models. More detailed models explain the nature of the complex computations performed by the cortical circuits and how the computations remain so remarkably robust in the face of a number of sources of noise, including variability in the anatomical connections, large variance in the synaptic responses and in the trial-to-trial output of single neurons, and weak or degraded input signals.