Classification of receptive field properties in cat visual cortex

Summary The properties of the receptive fields of visual cortex neurons of cats were studied manually and by a computer controlled system using single lines, double lines and multiple lines (gratings). The multiple selectivities of each of the receptive fields studied make it necessary to abandon the concept that each cell functions as a feature detector. Instead, an attempt was made to classify the receptive field properties with the aim to delineate the transfer functions (of the total networks) served by each property. When tested with one-line stimulus, cells with simple receptive field properties diffefed from cells with complex receptive field properties as to their velocity selectivity (simple: 1 ° to 3 °/s; complex: 4 ° to 10 °/s), spontaneous activity (lower for cells with simple properties), optimal firing rate (lower for cells with simple properties) and receptive field size (smaller for cells with simple properties) but not for orientation and direction selectivity. When tested with a 2-lines moving stimulus, the responses of cells with simple properties were facilitated by the progressive separation of the lines whereas the responses of cells with complex receptive field properties were inhibited. When multiple lines, i.e. gratings, were used, an equivalence between simple and X properties and complex and Y properties was shown, while the sustained/transient classification proved to be independent of the simple/complex (X/Y) classification. Thus, receptive field properties can be classified into three categories: one reflects the input to the receptive fields; a second deals with the interactive properties of the fields; while a third appears more related to the overall properties of the network.This research was supported by a postdoctoral fellowship from the Medical Research Council of Canada to Maurice Ptito, a predoctoral fellowship from the National Research Council of Canada to Maryse C. Lassende and NIMH Grant MH12970 and NIMH Career Research Award MH15214 to Karl H. Pribram