Choice Signals in The Visual Cortex

Post by Stephanie Williams

What's the science?

Activity in sensory brain areas can covary with perceptual choices, or “decisions”. The amount of decision-related information contained within visual brain areas that are early or mid-level in the brain’s visual processing stream is still under investigation. It is possible that choice-related information in these sensory areas could contain information about current choices as well as past choices (histories). Alternatively, they could only contain information related to the current choice. This week in the Journal of Neuroscience, Jasper, Tanabe and Kohn measured neurons in visual cortical regions and analyzed how well choice predictions could be made using information from (1) individual neurons, (2) populations of neurons and (3) choice and reward histories.

How did they do it?

The authors recorded from individual neurons and populations of neurons (up to 30 neurons) simultaneously in primary visual cortex (“V1”) and midlevel visual cortex ( “V4”) while macaque monkeys performed a visual orientation discrimination task. Two male monkeys were trained with liquid rewards to respond to a visual task that involved a circle with lines inside that appeared at different orientations (angles; called an ‘orientation grating’). In the task, two targets would appear after the orientation grating, and the monkeys would have to glance (called a “saccade”: a fast eye movement towards the target) upwards or downwards to the target that matched the orientation they had just seen, which the authors tracked with an eye-tracker. The authors trained the animals until they became “experts” at the task, reaching asymptotic performance. The authors note that in contrast to previous studies, which routinely tailor their tasks to the known responses of the neurons they record from, the authors did not choose this task based on the functional properties of the individual neurons they recorded from.

The authors implanted two 48 microelectrodes-arrays into the V1 and V4 regions of each animal. Monkey #1 had electrode arrays implanted first into the left hemisphere, and then implanted in the right hemisphere, resulting in 3 datasets (2 from Monkey #1, 1 from Monkey #2) in total. The authors mapped the spatial receptive fields of the neurons on the first day of the recording by showing the monkeys different gratings at different locations and orientations. The authors used the information from their electrophysiological recordings to predict the monkey’s behavioral choices. They were interested in understanding (1) How their predictions of the animal’s choice improved when they analyzed small populations of neurons rather than individual units and (2) How their predictions of the animal’s choice improved when they included the reward and choice history of the animal in their model. They also investigated whether the choice information in the neuronal responses reflected choice history. They used two choice history variables (each with values of -1 0 or 1) in their analyses, which contained information about the choice of the monkey on the previous trial, and whether the monkey received a reward.

What did they find?

The authors found that they could predict the animal’s responses using recordings of individual V4 neurons, but only if they looked at the time between the disappearance of the task (“stimulus offset”), and the choice that the monkey made, which was relatively late in the behavioral trial. They could not predict decisions with V1 neurons during the same time window. The authors had originally analyzed the window occurring  0-250 ms after stimulus onset, and found only weak choice prediction values in this window. They conclude from these results that there is choice information relayed by some V4 cells and that it occurs in the epoch between stimulus offset and the appearance of the choice targets.

When the authors considered populations of neurons rather than individual neurons, they found they could predict the monkey’s decisions. They found a weaker choice signal in V1 than in V4, despite the higher sensitivity to orientation in V1. This result led the authors to suggest that choice signals may be determined by the proximity of the population to the decision area than by the sensitivity of the neurons. They could improve their prediction of the animal’s choice by considering their choice and reward history. They didn’t find evidence that choice history was represented explicitly in V1 or V4, which is consistent with previous studies. Instead, they found that the component of the decision-related information that was incorporated in the sensory information was the decision at the current time.

What's the impact?

The authors show that both decision history and neuronal responses in visual areas can be used to predict perceptual decisions. They show that choice-related signals for this forced alternative task can be found in V4, but not in V1. These findings have important implications for understanding how decision information is processed in the brain, demonstrating how integrating information across neurons can be informative in predicting decision behavior.

Jasper et al. Predicting perceptual decisions using visual cortical population responses and choice history. J Neuroscience (2019). Access the original scientific publication here.