A Refined Neuronal Population Measure of Visual Attention

Neurophysiological studies of cognitive mechanisms such as visual attention typically ignore trial-by-trial variability and instead report mean differences averaged across many trials. Advances in electrophysiology allow for the simultaneous recording of small populations of neurons, which may obviate the need for averaging activity over trials. We recently introduced a method called the attention axis that uses multi-electrode recordings to provide estimates of attentional state of behaving monkeys on individual trials. Here, we refine this method to eliminate problems that can cause bias in estimates of attentional state in certain scenarios. We demonstrate the sources of these problems using simulations and propose an amendment to the previous formulation that provides superior performance in trial-by-trial assessments of attentional state

Hugh Borton oral histories conducted on October 12, 1973, March 14, 1980, and April 15 and 16, 1982.

Marlene Mayo, Professor of History of the University of Maryland, conducted interviews with Hugh Borton on October 12, 1973, March 14, 1980, and April 15 and 16, 1982 for a total of 7 hours, 29 minutes. Borton (1903 - 1995), a renowned scholar of Japanese history, was in the U.S. Department of State from 1942 to 1948, where he served as Chief of the Japanese Affairs Division and Special Assistant to the Director of Far Eastern Affairs. During his tenure at the State Department, he was instrumental in drafting proposals that would govern post-World War II Japan. Among them was the decision not to prosecute Emperor Hirohito, the re-writing of the Japanese constitution, and the drafting of the peace treaty

A Refined Neuronal Population Measure of Visual Attention

Neurophysiological studies of cognitive mechanisms such as visual attention typically ignore trial-by-trial variability and instead report mean differences averaged across many trials. Advances in electrophysiology allow for the simultaneous recording of small populations of neurons, which may obviate the need for averaging activity over trials. We recently introduced a method called the attention axis that uses multi-electrode recordings to provide estimates of attentional state of behaving monkeys on individual trials. Here, we refine this method to eliminate problems that can cause bias in estimates of attentional state in certain scenarios. We demonstrate the sources of these problems using simulations and propose an amendment to the previous formulation that provides superior performance in trial-by-trial assessments of attentional state

Behavioral performance as a function of attention axis position.

<p><i>Left</i>, Projections on the original attention axis for each stimulus location (Fig 2F from [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0136570#pone.0136570.ref005" target="_blank">5</a>]). Horizontal line indicates mean proportion correct across trials. <i>Right</i>, Same data combined across stimulus locations plotted on the original attention axis (red line) and re-plotted on the revised attention axis (blue line).</p

Multidimensional regression.

<p>The responses of two neurons in two conditions, attend-left and attend-right. Neuron 1’s response to attend-right is greater than that to attend-left, and its responses in both conditions are noiseless, as illustrated by the impulse functions (top) and vertical dashed lines. The response of neuron 2 is noiseless in the attend-left condition, but drawn from a uniform distribution in the attend-right condition (impulse function and spanned range on right). The attention axis (double-sided arrow) connects samples <i>A</i> and <i>B</i>.</p

Attention axis positions are correlated when the axis is constructed using neurons recorded from the same hemisphere, but uncorrelated for those across left (L) and right (R) hemispheres.

<p><b>(A)</b>, original attention axis, Fig 6 from [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0136570#pone.0136570.ref005" target="_blank">5</a>]. <b>(B)</b>, revised attention axis.</p