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Spatial and feature-selective attention have distinct effects on population-level tuning.

Goddard, E.; Carlson, T. A.; Woolgar, A.

2019-11-06 neuroscience
10.1101/530352 bioRxiv
Show abstract

Attention is a fundamental brain process by which we selectively prioritize relevant information in our environment. Cognitively, we can employ different methods for selecting visual information for further processing, but the extent to which these are implemented by similar or different neural processes remains unclear. Spatial and feature-selective attention both change the stimulus related information signaled by single-cells and neural populations, but relatively few studies have directly compared the effects of these distinct types of attention. We scanned participants (n=20) using MEG, while they covertly attended to an object on the left or the right of fixation (spatial attention manipulation) and reported the objects shape or color (feature-selective attention manipulation). We used multivariate pattern classification to measure population stimulus-coding in occipital and frontal areas, for attended and non-attended stimulus features, at attended and non-attended locations. In occipital cortex, we show that both spatial and feature-selective attention enhanced object representations, and the effects of these two attention types interacted multiplicatively. We also found that spatial and feature-selective attention induced qualitatively different patterns of enhancement in occipital cortex for the encoding of stimulus color. Specifically, feature-based attention primarily enhanced small color differences, while spatial attention produced greater enhancement for larger differences. We demonstrate that principles of response-gain and tuning curve sharpening that have been applied to describe the effects of attention at the level of a single neuron can account for these differences. An information flow analysis suggested that these attentional effects may be driven by feedback from frontal areas.

Published in Journal of Cognitive Neuroscience (predicted rank #2) · training set

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