A neuronal population measure of attention predicts behavioral performance on individual trials
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1
Harvard Medical School, United States
Internal states such as attention have dramatic effects on behavior. On blocks of trials when an animal directs attention to a particular area of space, perception at that location is greatly improved compared to blocks of trials when attention is directed elsewhere. Like all neuronal and behavioral processes, attention varies from moment to moment, but the behavioral consequences of fluctuations in attention within an attentional condition have been impossible to track using either psychometric performance, which by definition is measured over large numbers of trials. Previous studies have therefore only studied the effects of attention averaged over long periods. Because attention modulates the responses of sensory neurons, it should in principle be possible to detect fluctuations in attention by measuring neuronal responses. However, obtaining single trial estimates of attention is not possible from responses of a single neuron. Many sensory neurons are likely to contribute to any perceptual process, so trial-to-trial changes in single neuron responses should not be expected to strongly correlate with behavioral fluctuations caused by attention. More importantly, it is impossible to dissociate variability in single neuron responses due to attention from variability due to other factors. These problems may be solved by basing a single trial measure of attention on the responses of many simultaneously recorded neurons. We obtained a single trial metric of attention that quantified the similarity of responses of dozens of neurons in visual area V4 to mean responses in two attention conditions. We were able to show for the first time that the response of a modestly-sized population of sensory neurons can reliably predict an animal’s performance on a single trial. We found that within an attentional condition, this attentional modulation of a population of neurons varies substantially within and between trials, and that the monkey’s ability to detect a given small change in a stimulus varies from near perfect performance to near zero depending on the amount of modulation of the population. We also used this single trial measure to test the validity of the metaphor of an attentional "spotlight" that has been long used to describe visual attention, which suggests that attention is a limited resource that can be directed to a specific location or small set of locations. Implicit in this idea is the assumption that increasing attention to one location reduces attention at other locations, so the amount of attention allocated to two locations should typically be anticorrelated. By simultaneously recording the responses of populations of neurons in opposite hemispheres, we were able to test this assumption directly. Unexpectedly, we found that on a trial-to-trial basis, the amount of attention allocated to two locations in opposite hemifields was uncorrelated, suggesting that at any moment attention is allocated to each spatial location independently. Consistent with recent proposals that attention acts through the same mechanisms that control response normalization, these results suggest that attention to locations in opposite hemifields is governed not by a single top-down control mechanism, but by local groups of neurons whose variability is independent.
Conference:
Computational and Systems Neuroscience 2010, Salt Lake City, UT, United States, 25 Feb - 2 Mar, 2010.
Presentation Type:
Poster Presentation
Topic:
Poster session III
Citation:
Cohen
MR and
Maunsell
JH
(2010). A neuronal population measure of attention predicts behavioral performance on individual trials.
Front. Neurosci.
Conference Abstract:
Computational and Systems Neuroscience 2010.
doi: 10.3389/conf.fnins.2010.03.00256
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Received:
05 Mar 2010;
Published Online:
05 Mar 2010.
*
Correspondence:
Marlene R Cohen, Harvard Medical School, Boston, United States, marlene_cohen@hms.harvard.edu