The magnitude and apparent complexity of the brain's connectivity have left explicit networks largely unexplored. As a result, the relationship between the organization of synaptic connections and how the brain processes information is poorly understood. A recently proposed retinal network that produces neural correlates of color vision is refined and extended here to a family of general logic circuits. For any combination of high and low activity in any set of neurons, one of the logic circuits can receive input from the neurons and activate a single output neuron whenever the input neurons have the given activity state. The strength of the output neuron's response is a measure of the difference between the smallest of the high inputs and the largest of the low inputs. The networks generate correlates of known psychophysical phenomena. These results follow directly from the most cost-effective architectures for specific logic circuits and the minimal cellular capabilities of excitation and inhibition. The networks function dynamically, making their operation consistent with the speed of most brain functions. The networks show that well-known psychophysical phenomena do not require extraordinarily complex brain structures, and that a single network architecture can produce apparently disparate phenomena in different sensory systems.
9The human brain is widely regarded as the most complex known object. However, without 10 details such as redundancies and other error-correcting mechanisms, the basic organization of 11 synaptic connections within the building blocks is likely to be less complex than it appears. For 12 some brain functions, the network architectures can even be quite simple. The flip-flop and 13 oscillator models proposed here are composed of two to six neurons, and their operation depends 14 only on the minimal neuron capabilities of excitation and inhibition. These networks generate 15 neural correlates of so many major phenomena of short-term memory and electroencephalography 16 in such detail that the possibility of the brain producing the phenomena with fundamentally 17 different network architectures is remote. For example, cascaded oscillators can produce the 18 periodic activity commonly known as brainwaves by enabling the state changes of many networks 19 simultaneously. (The function of such oscillator-induced synchronization in information 20 processing systems is timing error avoidance.) Then the boundary separating the alpha and beta 21 frequency bands is 22 29
BackgroundTwo previous articles proposed an explicit model of how the brain processes information by its organization of synaptic connections. The family of logic circuits was shown to generate neural correlates of complex psychophysical phenomena in different sensory systems.Methodology/Principal FindingsHere it is shown that the most cost-effective architectures for these networks produce correlates of electrophysiological brain phenomena and predict major aspects of the anatomical structure and physiological organization of the neocortex. The logic circuits are markedly efficient in several respects and provide the foundation for all of the brain's combinational processing of information.Conclusions/SignificanceAt the local level, these networks account for much of the physical structure of the neocortex as well its organization of synaptic connections. Electronic implementations of the logic circuits may be more efficient than current electronic logic arrays in generating both Boolean and fuzzy logic.
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