A Unifying Mechanistic Model of Selective Attention in Spiking Neurons

Bruce Bobier, Terrence C Stewart and Chris Eliasmith

PLOS Computational Biology, 2014, vol. 10, issue 6, 1-16

Abstract: Visuospatial attention produces myriad effects on the activity and selectivity of cortical neurons. Spiking neuron models capable of reproducing a wide variety of these effects remain elusive. We present a model called the Attentional Routing Circuit (ARC) that provides a mechanistic description of selective attentional processing in cortex. The model is described mathematically and implemented at the level of individual spiking neurons, with the computations for performing selective attentional processing being mapped to specific neuron types and laminar circuitry. The model is used to simulate three studies of attention in macaque, and is shown to quantitatively match several observed forms of attentional modulation. Specifically, ARC demonstrates that with shifts of spatial attention, neurons may exhibit shifting and shrinking of receptive fields; increases in responses without changes in selectivity for non-spatial features (i.e. response gain), and; that the effect on contrast-response functions is better explained as a response-gain effect than as contrast-gain. Unlike past models, ARC embodies a single mechanism that unifies the above forms of attentional modulation, is consistent with a wide array of available data, and makes several specific and quantifiable predictions.Author Summary: At a given moment, a tremendous amount of visual information falls on the retinae, far more than the brain is capable of processing. By directing attention to a spatial location, stimuli at that position can be selectively processed, while irrelevant information from non-attended locations can be largely ignored. We present a detailed model that describes the mechanisms by which visual spatial attention may be implemented in the brain. Using this model, we simulated three previous studies of spatial attention in primates, and analysed the simulation data using the same methods as in the original experiments. Across these simulations, and without altering model parameters, our model produces results that are statistically indistinguishable from those recorded in primates. Unlike previous work, our model provides greater biological detail of how the brain performs selective visual processing, while also accurately demonstrating numerous forms of selective attention. Our results suggest that these seemingly different forms of attentional effects may result from a single mechanism for selectively processing attended stimuli.

Date: 2014
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Persistent link: https://EconPapers.repec.org/RePEc:plo:pcbi00:1003577

DOI: 10.1371/journal.pcbi.1003577

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