Multiple-object working memory--a model for behavioral performance.

D J Amit; A Bernacchia; V Yakovlev

doi:10.1093/cercor/13.5.435

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Multiple-object working memory--a model for behavioral performance.

D J Amit·A Bernacchia·V Yakovlev

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Abstract

In a psychophysics experiment, monkeys were shown a sequence of two to eight images, randomly chosen out of a set of 16, each image followed by a delay interval, the last image in the sequence being a repetition of any (one) of the images shown in the sequence. The monkeys learned to recognize the repetition of an image. The performance level was studied as a function of the number of images separating cue (image that will be repeated) from match for different sequence lengths, as well as at fixed cue-match separation versus length of sequence. These experimental results are interpreted as features of multi-item working memory in the framework of a recurrent neural network. It is shown that a model network can sustain multi-item working memory. Fluctuations due to the finite size of the network, together with a single extra ingredient, related to expectation of reward, account for the dependence of the performance on the cue-position, as well as for the dependence of performance on sequence length for fixed cue-match separation.

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Animals Cues Haplorhini Memory Neural Networks, Computer Photic Stimulation Recognition, Psychology Journal Article

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D J Amit, A Bernacchia, V Yakovlev. 2003. Multiple-object working memory--a model for behavioral performance.. https://doi.org/10.1093/cercor%2F13.5.435

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