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Summary
Connection from neuron to neuron in the cortex of the brain becomes less effective with each successive action potential but eventually recovers after the end of the action potential burst. Two new reports, one in this issue (p. 220), present many-neuron models with these properties and show that these neurons respond to large changes in the frequency of individual inputs (they act as frequency detectors) or to simultaneous changes in many inputs (they act as coincidence detectors). In her Perspective, Thomson explains the origin of the modeled properties and discusses the accuracy with which these models mimic the behavior of real cortical cells. Such modeling of many neurons with real properties reveals computational characteristics of the circuit not apparent from analyses of individual cells.
