A principle advantage of our technique is that it allows the simultaneous recording of case position, pupil size, and single neurons in patients implanted with depth electrodes at the bedside. This allows us to determine whether there are neurons in the human brain whose activity is sensitive to eye movements and to the identity of the currently fixated stimulus. While this technique is not designed to study a particular disease, it is well-suited to study neurological diseases that result in abnormal eye movements or other ocular motor abnormalities.
Demonstrating the procedure will be Nand Chandravadia and James Lee, research associates from my laboratory. And Erika Quan, a neurodiagnostic technician at Cedars-Sinai. To begin, connect the electrodes to the recording system and position the patient sitting upright.
Then, connect the stimulus computer to the electrophysiology system and eye tracker. Place the remote non-invasive infrared eye tracking system on a robust mobile cart. Then, attach a flexible arm that holds an LCD display to the cart.
Place a fully charged uninterrupted power supply on the eye tracking cart and connect all devices related to eye tracking to the power supply rather than to an external power source. Make sure the IV device connected to the patient is running on battery and is not plugged into the wall. Start the eye tracking software.
Adjust the distance between the patient and the LCD screen to between 60 and 70 centimeters. Also adjust the angle of the LCD screen so that the surface of the screen is approximately parallel to the patient's face. Place a sticker on the patient's forehead so that the eye tracker can adjust for head movements.
Now, adjust the height of the screen relative to the patient's head such that the camera of the eye tracker is approximately at the height of the patient's nose. Provide the patient with a button box or keyboard. Verify that triggers and button press are recorded properly before starting the experiment.
Start the acquisition software. First visually inspect the broadband local field potentials and make sure they are not contaminated by line noise. Otherwise follow standard procedures to remove noise.
To identify single-neurons, band pass filter the signal from 300 hertz to eight kilohertz. Select one of the eight microwires as a reference for each microwire bundle. Enable saving the data as an nrd file before recording.
Adjust the distance and angle between the eye tracker and the patient so that the target marker, head distance, pupil, and corneal reflection are marked as ready. This is shown in green in the eye tracking software. Click on the eye to be recorded and set the sampling rate to 500 hertz.
Use the auto adjustment of the pupil and corneal reflection threshold. Calibrate the eye tracker with the built-in grid method at the beginning of each block. Confirm the eye positions register nicely as a grid.
Otherwise, redo the calibration. Accept the calibration and do the validation. Accept the validation if the maximal validation error is less than two degrees and the average validation error is less than one degree.
Otherwise, redo the validation. Then, perform drift correction and proceed to the actual experiment. In this visual search task, use the stimuli from a previous study performed by this group and follow the task procedure as described before.
Provide task instructions to the participants. Instruct the participants to find a target item in the search array and respond as soon as possible. Instruct the participants to press the left button of a response box if they find the target and press the right button if they think the target is absent.
Explicitly instruct the participants that there will be target-present and target-absent trials. Start stimulus presentation software and run the task. Present a target cue for one second and present the search array using the stimulus presentation software.
Record the button presses and provide trial by trial feedback to the participants. To illustrate the usage of this method, 228 single neurons were recorded from the human medial temporal lobe while patients were performing a visual search task as shown here. During this task, it was investigated whether the activity of neurons differentiated between fixations on targets and distractors.
When responses were aligned at the button press, neurons were found that showed differential activity between target-present trials and target-absent trials. Black lines represent the onset and offset of the search queue. This neuron increased its firing rate for target-present trials but not for target-absent trials.
Conversely, this neuron decreased its firing rate for target-present trials but not for target-absent trials. A subset of medial temporal lobe neurons showed significantly different activities between fixations on targets versus distractors. Furthermore, one type of such target neuron had a greater response to targets relative to distractors whereas the other had a greater response to distractors relative to targets.
Together, this result demonstrates that a subset of medial temporal lobe neurons encode whether the present fixation landed on a target or not. It is critical to make sure that the eye tracker does not introduce noise into the recording. Any noise must be removed before the experiments are performed.
If noise persists, ensure the screen used to display the stimulus to the subject has an external power supply. Exchange power supplies for more high quality power supplies typically used for high-end audio applications. Following this procedure, analysis of spikes and eye movements are performed to extract information from the data that will allow researcher to investigate the neuronal responses to eye movements.
This method paves the way to explore many unanswered questions that require analysis of fixations, such as how neurons collectively drive fixations to interesting objects in a scene.
