Neural Networks: Artificial Intelligence and Industrial Applications
Synchronized oscillatory activity in the visual system has been proposed as a temporal label of feature-linking, by assuming that spatial segmentation coding of a visual scene is based on synchronized oscillations within a segment's neural representation and on desynchronized signals among different segments. In an extended hypothesis it was stated that segmentation may be based on any type of synchronization and desynchronization, being rhythmical or non-rhythmical, stimulus-dominated or internally generated. This was supported by experimental evidence obtained by multiple microelectrode recordings from the visual cortex of cats and monkeys. It includes stimulus specific synchronization and facilitation at zero-delay correlation during short stimulus-locked responses and during sustained oscillations (35-90 Hz). We now extend the synchronization hypothesis to spatio-temporal segmentation coding by suggesting that the synchronized single or repetetive interruptions of excitations define temporally precise internal representations. By applying this to natural vision, we can argue that during phases of slowly changing retinal images (like ocular fixation and smooth pursuit) oscillations may prevent perceptual "smearing" by interrupting the flow of visual information repetetively. However, when a visual object suddenly changes its position, ongoing oscillations should immediately be interrupted by the single excitation-inhibition cycle evoked by the objects displacement. Such stimulus-locked cycles might acts as "reset" signals of prior, and evoke new, segmentations of an object against the remaining scene. Experimental evidence in support of this hypothesis includes our observations on suppression of oscillatory by stimuluslocked responses and on changes of oscillation frequencies with velocity, size and intensity of a stimulus.