Abstract
The local field potential (LFP) has recently been widely used in brain computer interfaces (BCI). Here we used power of LFP recorded from area MT of a macaque monkey to decode where the animal covertly attended. Support vector machines (SVM) were used to learn the pattern of power at different frequencies for attention to two possible positions. We found that LFP power at both low (<9 Hz) and high (31–120 Hz) frequencies contains sufficient information to decode the focus of attention. Highest decoding performance was found for gamma frequencies (31–120 Hz) and reached 82%. In contrast low frequencies (<9 Hz) could help the classifier reach a higher decoding performance with a smaller amount of training data. Consequently, we suggest that low frequency LFP can provide fast but coarse information regarding the focus of attention, while higher frequencies of the LFP deliver more accurate but less timely information about the focus of attention.
Highlights
Attention as a filtering mechanism selects behaviorally relevant stimuli for more effective processing in the mammalian cortex
We investigated whether local field potential (LFP) recorded from the visual cortex of a macaque monkey can be used to decode the focus of attention, and compared the contribution of different frequency bands to the performance of decoding
We found that the power of LFPs at different frequencies can be used to decode the focus of attention with appreciable performance, where gamma frequencies (31–120 Hz) had the highest performance
Summary
Attention as a filtering mechanism selects behaviorally relevant stimuli for more effective processing in the mammalian cortex. The most basic neuronal correlate of attention has been reported as the increase in firing rate of neurons that are selective to the feature or position that the animal has attended to This effect has been reported in different visual areas of macaques [3], [4]. Previous studies have shown that spatial attention is correlated with an increase in high frequency oscillations and decrease in low frequency oscillations in LFPs of the visual cortex [8,9,10], albeit see [13] for different results. It is assumed that attention modulates local cortical activities by controlling the phase of low frequency oscillations which are functionally involved in the processing of stimuli [15], [17]
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