Method Article

Simultaneous Eye Tracking and Single-Neuron Recordings in Human Epilepsy Patients

DOI:

10.3791/59117

⸱

June 17th, 2019

 ,  ,  , 
1Department of Chemical and Biomedical Engineering, and Rockefeller Neuroscience Institute, West Virginia University, 2Departments of Neurosurgery and Neurology, Cedars-Sinai Medical Center, 3Center for Neural Science and Medicine, Department of Biomedical Sciences, Cedars-Sinai Medical Center, 4Division of Biology and Biological Engineering, California Institute of Technology

In This Article

Summary

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We describe a method to conduct single-neuron recordings with simultaneous eye tracking in humans. We demonstrate the utility of this method and illustrate how we used this approach to obtain neurons in the human medial temporal lobe that encode targets of a visual search.

Abstract

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Intracranial recordings from patients with intractable epilepsy provide a unique opportunity to study the activity of individual human neurons during active behavior. An important tool for quantifying behavior is eye tracking, which is an indispensable tool for studying visual attention. However, eye tracking is challenging to use concurrently with invasive electrophysiology and this approach has consequently been little used. Here, we present a proven experimental protocol to conduct single-neuron recordings with simultaneous eye tracking in humans. We describe how the systems are connected and the optimal settings to record neurons and eye movements. To illustrate the utility of this method, we summarize results that were made possible by this setup. This data shows how using eye tracking in a memory-guided visual search task allowed us to describe a new class of neurons called target neurons, whose response was reflective of top-down attention to the current search target. Lastly, we discuss the significance and solutions to potential problems of this setup. Together, our protocol and results suggest that single-neuron recordings with simultaneous eye tracking in humans are an effective method to study human brain function. It provides a key missing link between animal neurophysiology and human cognitive neuroscience.

Introduction

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Human single-neuron recordings are a unique and powerful tool to explore the function of the human brain with extraordinary spatial and temporal resolution1. Recently, single-neuron recordings have gained wide use in the field of cognitive neuroscience because they permit the direct investigation of cognitive processes central to human cognition. These recordings are made possible by the clinical need to determine the position of epileptic foci, for which depth electrodes are temporarily implanted into the brains of patients with suspected focal epilepsy. With this setup, single-neuron recordings can be obtained using microwires protruding from the tip of the hybrid depth electrode (a detailed description of the surgical methodology involved in the insertion of hybrid depth electrodes is provided in the previous protocol2). Among others, this method has been used to study human memory3,4, emotion5,6, and attention7,8.

Eye tracking measures gaze position and eye movements (fixations and saccades) during cognitive tasks. Video-based eye trackers typically use the corneal reflection and the center of the pupil as features to track over time9. Eye tracking is an important method to study visual attention because the gaze location indicates the focus of attention during most natural behaviors10,11,12. Eye tracking has been used extensively to study visual attention in healthy individuals13 and neurological populations14,15,16.

While both single-neuron recordings and eye tracking are individually used extensively in humans, few studies have used both simultaneously. As a result, it still remains largely unknown how neurons in the human brain respond to eye movements and/or whether they are sensitive to the currently fixated stimulus. This is in contrast to studies with macaques, where eye-tracking with simultaneous single-neuron recordings has become a standard tool. In order to directly investigate the neuronal response to eye movements, we combined human single-neuron recordings and eye tracking. Here we describe the protocol to conduct such experiments and then illustrate the results through a concrete example.

Despite the established role of the human medial temporal lobe (MTL) in both object representation17,18 and memory3,19, it remains largely unknown whether MTL neurons are modulated as a function of top-down attention to behaviorally relevant goals. Studying such neurons is important to start to understand how goal-relevant information influences bottom-up visual processes. Here, we demonstrate the utility of eye tracking while recording neurons using guided visual search, a well-known paradigm to study goal-directed behavior20,21,22,23,24,25. Using this method, we recently described a class of neurons called target neurons, which signals whether the currently attended stimulus is the goal of an ongoing search8. In the below, we present the study protocol needed to reproduce this previous scientific study. Note that along this example, the protocol can easily be adjusted to study an arbitrary visual attention task.

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Protocol

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1. Participants

  1. Recruit neurosurgical patients with intractable epilepsy who are undergoing placement of intracranial electrodes to localize their epileptic seizures.
  2. Insert depth electrodes with embedded microwires into all clinically indicated target locations, which typically include a subset of amygdala, hippocampus, anterior cingulate cortex and pre-supplementary motor area. See details for implantation in our previous protocol2.
  3. Once the patient returns to the epilepsy monitoring unit, connect the recording equipment for both macro- and micro- recordings. This includes carefully preparing a head-wrap that includes head stages (see our previous description for details2). Then, wait for the patient to recover from the surgery and conduct testing when the patient is fully awake (typically at least 36 to 48 h after surgery).

2. Experimental setup

  1. Connect the stimulus computer to the electrophysiology system and eye tracker following the diagram in Figure 1.
  2. Use the remote non-invasive infrared eye tracking system (see Table of Materials). Place the eye tracking system on a robust mobile cart (Figure 1A, B). To the same cart, attach a flexible arm that holds an LCD display. Use the remote mode to track the patients head and eyes.
  3. Place a fully charged uninterrupted power supply (UPS) on the eye tracking cart and connect all devices related to eye tracking (i.e., LCD in front of patient, eye tracker camera and light source, and eye tracker host computer) to the UPS rather than to an external power source.
  4. Adjust the distance between the patient and the LCD screen to 60-70 cm and adjust the angle of the LCD screen so that the surface of the screen is approximately parallel to the patient’s face. 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.
  5. Provide the patient with the button box or keyboard. Verify that triggers (TTLs) and button press are recorded properly before starting the experiment.

3. Single-neuron recording

  1. Start the acquisition software. First, visually inspect the broadband (0.1 Hz - 8 kHz) local field potentials and make sure they are not contaminated by line noise. Otherwise, follow standard procedures to remove noise (see Discussion).
  2. To identify single neurons, band-pass filter the signal (300 Hz - 8 KHz). Select one of the eight microwires as a reference for each microwire bundle. Test different references and adjust the reference so that (1) the other 7 channels show clear neurons, and (2) the reference does not contain neurons. Set the input range to be ± 2,000 µV.
  3. Enable saving the data as an NRD file (i.e., the broadband raw data file that will be used for subsequent off-line spike sorting) before recording data. Set the sampling rate to 32 kHz.

4. Eye tracking

  1. Start the eye tracking software. Because it is a head-fixation free system, place the sticker on the patient’s forehead so that the eye tracker can adjust for head movements.
  2. Adjust the distance and angle between the eye tracker and patient so that the target marker, head distance, pupil, and corneal reflection (CR) are marked as ready (as shown in green in the eye tracking software; Figure 2 shows a good example camera setup screen). Click on the eye to be recorded and set the sampling rate to 500 Hz.
  3. Use the auto-adjustment of pupil and CR threshold. For patients wearing glasses, adjust the position and/or angle of the illuminator and camera so that reflections from the glass will not interfere with pupil acquisition.
  4. Calibrate the eye tracker with the built-in 9-point grid method at the beginning of each block. Confirm that eye positions (shown as “+”) register nicely as a 9-point grid. Otherwise, redo calibration.
  5. Accept the calibration and do validation. Accept the validation if the maximal validation error is < 2° and the average validation error is < 1°. Otherwise, redo validation.
  6. Do drift correction and proceed to the actual experiment.

5. Task

  1. In this visual search task, use the stimuli from our previous study14 and follow the task procedure as described before8.
  2. Provide task instructions to participants. Instruct the participants to find the target item in the search array and respond as soon as possible. Instruct the participants to press the left button of a response box (see Table of Materials) if they find the target and the right button if they think the target is absent. Explicitly instruct the participants that there will be target-present and target-absent trials.
  3. Start stimulus presentation software (see Table of Materials) and run the task: Present a target cue for 1 s and present the search array using the stimulus presentation software. Record button presses and provide trial-by-trial feedback (Correct, Incorrect, or Time Out) to participants.

6. Data analysis

  1. Because the acquisition and eye tracking systems run on different clocks, use the behavioral log file to find the alignment timestamp for electrophysiology recording and eye tracking. Match the triggers from electrophysiology recording and eye tracking before proceeding to further analysis. Extract segments of data according to timestamps and analysis windows separately for electrophysiology recording and eye tracking.
  2. Use the semi-automatic template matching algorithm Osort26 and follow the steps described before2,26 to identify putative single neurons. Assess the quality of the sorting before moving to further analysis2.
  3. To analyze eye movement data, first convert the EDF data from the eye tracker into ASCII format. Also, extract fixations and saccades. Then, import the ASCII file and save the following information into a MAT file: (1) time stamps, (2) eye coordinates (x,y), (3) pupil size, and (4) event time stamps. Parse the continuous recording into each trial.
  4. Follow previously described procedures to analyze the correlation between spikes and behavior8.

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Results

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To illustrate the usage of the above-mentioned method, we next briefly describe a use-case that we recently published8. We recorded 228 single neurons from the human medial temporal lobe (MTL; amygdala and hippocampus) while the patients were performing a visual search task (Figure 3A, B). During this task, we investigated whether the activity of neurons differentiated between fixations on targets and distractors.

...

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Discussion

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In this protocol, we described how to employ single-neuron recordings with concurrent eye tracking and described how we used this method to identify target neurons in the human MTL.

The setup involves three computers: one executing the task (stimulus computer), one running the eye tracker, and one running the acquisition system. To synchronize between the three systems, the parallel port is used to send TTL triggers from the stimulus computer to the electrophysiology system (

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Disclosures

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The authors declare no conflict of interest.

Acknowledgements

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We thank all patients for their participation. This research was supported by the Rockefeller Neuroscience Institute, the Autism Science Foundation and the Dana Foundation (to S.W.), an NSF CAREER award (1554105 to U.R.), and the NIH (R01MH110831 and U01NS098961 to U.R.). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. We thank James Lee, Erika Quan, and the staff of the Cedars-Sinai Simulation Center for their help in producing the demonstration video.

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Materials

List of materials used in this article
NameCompanyCatalog NumberComments
Cedrus Response BoxCedrus (https://cedrus.com/)RB-844Button box
Dell LaptopDell (https://dell.com)Precision 7520Stimulus Computer
EyeLink Eye TrackerSR Research (https://www.sr-research.com)1000 Plus Remote with laptop host computer and LCD arm mountEye tracking
MATLABMathWorks IncR2016a (RRID: SCR_001622)Data analysis
Neuralynx Neurophysiology SystemNeuralynx (https://neuralynx.com)ATLAS 128Electrophysiology
OsortOpen sourcev4.1 (RRID: SCR_015869)Spike sorting algorithm
Psychophysics ToolbxOpen sourcePTB3 ( RRID: SCR_002881)Matlab toolbox to implement psychophysical experiments

References

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Tags

Single Neuron RecordingsEye TrackingHuman Epilepsy PatientsMedial Temporal LobeVisual Search TaskTarget NeuronsIntracranial RecordingsElectroencephalographyPupil Size MonitoringStimulus Presentation Software

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