Investigating Object Representations in the Macaque Dorsal Visual Stream Using Single-unit Recordings

This method can help answering key questions in visual and motor systems neuroscience. For example, how do neurons encode objects and and object parts? And how do neural representations change from visual to motor?

The main advantage of this method is that neurons can be studied with real-world objects during reaching and grasping, and with images of objects and object parts presented on a display. Demonstrating this procedure will be Maria Romero, a postdoc, and Irene Caprara, a PhD student from my laboratory. Begin with the test subject situated in the testing chair in front of the object-grasping setup.

Adjust an infrared camera in front of the subject's eyes to obtain an adequate image of the pupil and corneal reflex. To run the visually-guided grasping task using a carousel setup, first allow the macaque to place the hand contralateral to the recorded hemisphere in the resting position in complete darkness to initiate the sequence. After a variable intertrial interval of 2, 000 to 3, 000 milliseconds, apply a red laser as a fixation point at the base of the object.

If the animal maintains its gaze inside an electronically-defined fixation window for 500 milliseconds, illuminate the object from above with a light source. Then, after a variable delay of 300 to 1, 500 milliseconds, program a dimming of the laser as the visual go cue. Instruct the macaque to lift the hand from the resting position and reach, grasp, and hold the object for a randomized variable interval of 300 to 900 milliseconds.

Whenever the macaque performs the whole sequence correctly, reward it with a drop of juice. As for the carousel setup, let the macaque place the hand contralateral to the recorded hemisphere in the resting position in complete darkness to initiate the sequence. After 2, 000 to 3, 000 milliseconds, illuminate the LED on the object.

Again, if the animal maintains its gaze inside an electronically-defined fixation window, illuminate the object with a white light source. After the delay, switch off the LED as the visual go cue. Again, the monkey lifts the hand from the resting position and reaches, grasps, and holds the object.

Reward the monkey with a drop of juice after each correct sequence. Continue the training with additional objects. During the task, the software should measure the reaction time between the go signal and the onset of the hand movement.

And the grasping time between the start of the movement and lifting of the object. For the 2D tasks, use a standard LCD monitor. Project all visual stimuli on a black background.

For the 3D tests, locate two ferroelectric liquid crystal shutters in front of the monkey's eyes. For the 3D test, locate two ferroelectric liquid crystal shutters in front of the monkey's eyes. Present the stimuli stereoscopically by alternating the left and right eye images on a cathode ray tube monitor equipped with a fast-decay P46 phosphor, while operating the shutters at 60 hertz with synchronization to the vertical retrace of the monitor.

Start the trial by presenting a small square in the center of the screen as the fixation point. If the eye position remains within an electronically-defined one-degree-square window for at least 500 milliseconds, present the visual stimulus on the screen for a total time of 500 milliseconds. When the monkey maintains a stable fixation until the stimulus offset, reward it with a drop of juice.

To study shape selectivity, run multiple tests with 2D images during the passive fixation task beginning with a search test. Test the visual selectivity of the cell using a wide set of images, including pictures of the object that was grasped in the VGG. For this and all subsequent visual tasks, compare the image evoking the strongest response, termed preferred image, to a second image to which the neuron is responding weakly, termed nonpreferred image.

Next, run a contour test. From the original surface images of real objects, obtain progressively simplified versions of the same stimulus shape. Collect at least 10 trials per condition.

To determine whether the neuron prefers the original surface, the silhouette, or the outline from the original shape. Then run a receptive field test. Present the images of objects at different positions on a display, covering the central visual field.

A total of 35 positions at three degrees are used here. Finally, run a reduction test with contour fragments presented at the center of the receptive field to identify the minimum effective shape feature. Determine the minimum effective shape feature as the smallest shape fragment evoking a response that is at least 70%of the intact outline response.

This image shows the responses of an example neuron recorded from area F5p, tested with a sphere and a plate, shown in two different sizes. This particular neuron responded not only to the large sphere optimal stimulus, but also to the large plate. In comparison, the response to the smaller objects was weaker.

The following images show results from an example neuron recorded in the anterior intraparietal area, and tested during both the visually-guided grasping task and passive fixation. This neuron was responsive during grasping. The neuron was also responsive to the visual presentation of 2D images of objects, including pictures of the objects used in the grasping task.

The preferred was not the object to be grasped, but another 2D picture with which the animal had no previous grasping experience. An example of the responses obtained in the reduction test is shown here. This example neuron responded to the smallest fragments in the test.

Once mastered, this technique can be done in less than 90 minutes, if it's performed correctly. After watching this video, you should have a good understanding of how to test neurons in the dorsal visual stream with objects and images of objects to determine the critical features that drive the responses.