Potentiels liés à l'événement et paradigme "oddball" (ou stimulus discordant)

Given the overwhelming amount of sensory information in our environment, the brain must be able to prioritize the processing of certain stimuli, so that it spends less effort on what might not be currently important, and attend to what is.

Everyday, a person is exposed to multiple sights and sounds, like people typing in the office or visuals on a computer screen.

The attention someone pays to such stimuli depends, in part, on their goals at any given moment. For example, they may purposefully focus on their monitor to review a presentation. When this happens, the brain ignores frequent, unimportant items—like the typing of coworkers—and instead attends to the slides on the screen.

This is an example of a process called top-down attention, in which the brain filters out information not related to a goal.

In contrast, bottom-up attention deals with unique, unexpected stimuli, which have the ability to capture a person’s attention, even though they aren’t related to an objective.

These rare noises or sights are called oddball stimuli, and—due to their novelty—are prioritized by the brain for processing, as they may be important. A noise in the kitchen might mean that someone is hurt, or that there may be snacks.

In response to such important sensory events—the crash in the kitchen—multiple neurons in the same region of the brain can be activated, which promotes the propagation of an electrical signal.

This electrical response can be gauged at the scalp with electrodes through techniques of electroencephalography—abbreviated as EEG—and the resulting measure is called an event-related potential, or ERP.

In this video, we will investigate ERPs during an oddball paradigm, in which subjects are shown unique and common visual stimuli. We will demonstrate how to setup an EEG experiment, analyze ERP data, and explore how researchers are applying this technique to study other aspects of attention.

In this experiment, the brain activity of participants viewing two types of shape-based stimuli—baseline and oddball—is measured using EEG, in order to gain insight into how the brain identifies irrelevant from important sensory information.

To prepare for EEG, researchers position electrodes—already inserted into a cap—on participants’ scalps at specific anatomical locations, so that electrical activity in the brain can be recorded.

Additional electrodes are placed around the eyes to gauge muscle activity—which can produce motion artifacts in EEG data—and behind the ears at mastoid locations that serve as references where non-neural information is gathered.

Participants are then introduced to the two types of stimuli they’ll be seeing. Here, baseline visuals consist of a single, red circle, whereas an oddball image is composed of an individual green circle.

Participants are instructed to be on the lookout for green shapes, and directed to push a button whenever one is shown onscreen.

During the task, each circle appears for 1 s on a computer monitor. After the circle disappears, the screen remains blank for 1 s, and the next image is then presented.

The trick is that participants are shown green circles sporadically—and much less often—between several sequential images of red ones. Of the 160 stimuli, only 64 are green.

The idea is that these "out-of-place" target images will capture both bottom-up attention—as they are rare—and top-down attention—as the goal of the task is to indicate when these shapes appear.

As a result, the brain will respond to these goal-related, potentially important stimuli by producing robust electrical signals.

EEG data are continuously recorded over all 160 trials. Then, the sequence is repeated and a second set of 160 images is shown, which ensures that enough information is collected to distinguish true oddball-induced activity from noise.

Afterwards, EEG data are processed to generate ERP waveforms for each anatomical site over which an electrode is placed.

Based on previous research, the most critical data are expected near the Pz electrode, located in the center of the scalp towards the back of the head, above the junction of the parietal lobes.

Specifically, one component of these parietal ERPs, called P300—so named because it consists of a positive peak in the waveform that occurs approximately 300 ms after a sensory stimulus is presented—are predicted to be enhanced in response to green oddball circles.

To begin the experiment, greet the participant and ensure that they sign all appropriate consent forms. Also confirm that they have not used any hair products, such as mousse, which could interfere with EEG recordings.

Before proceeding, first stir the conductive electrode-gel to release any air bubbles. Then, use it to fill a 10 ml syringe, which will aid in applying this substance to electrode arrangements later in the protocol.

Once the syringe has been prepared, thoroughly brush the participant’s hair and scalp, and clean the top of their head with cotton gauze soaked in alcohol.

Afterwards, sterilize the skin behind each of the participant’s ears above and below the left eye and at the far horizontal positions of both eyes in a similar manner.

Next, place one face of a two-sided adhesive disk against an electrode. On the other side, apply gel onto the exposed electrode, and then affix it to the cleaned area above the left eye. Repeat this process at the remaining sterilized positions on the face.

To determine the size of the EEG cap to be used, measure the distance from the front of the participant’s head—directly between the eyebrows—to the inion projection of the skull, located below the bump at the back of the head. Above the mid-eye point, mark 10% of the measured distance on the forehead.

Using the eye-to-inion measurement, choose a cap that fits within standard circumference ranges, and place it so that the FPz electrode—the central, front-most one—is positioned over the mark on the forehead. Then, connect each of the face electrodes to its respective cord on the cap.

After retrieving the gel-filled syringe, inform the participant that you’ll be inserting the blunted tip into every electrode. Now, lift each one, and scrape the underlying hair aside, being careful not to injure the skin.

Then, proceed to insert the gel, and repeat this process for the remaining cap electrodes to ensure that the electrical signals collected at the scalp are properly conducted.

Afterwards, take the participant to a quiet room with acoustic and electrical shielding, and plug in the entire cap into the recording system.

Using the associated computer program, check the impedances of the electrode-scalp connections. If the impedance is above 10 KΩ for any electrode—which can result in noise in EEG traces—verify that it has conductive gel and that all of the underlying hair has been moved away.

Note that all impedance values should now be below 10 KΩ.

In preparation for the behavioral task, have the participant sit so that they are positioned approximately 75 cm from the monitor, and give them a response box to hold. Emphasize that they should only press the timing button when they observe a green circle onscreen.

After the participant understands the task, start the EEG system. Allow them to complete the 64 target stimulus trials interspersed with the 96 non-target control trials. Following the 160 trials, initiate the sequence to repeat.

Once all of the data have been collected, import the results into an analysis program to begin offline processing. First, isolate only the neural signals by referencing the information to averaged mastoid values.

Continue by dividing the continuous EEG recordings into epochs—sections beginning 200 ms before and ending 1000 ms after the onset of every stimulus, in this instance either green or red circles.

Proceed to baseline adjust these time frames using the portions that occur 200 ms prior to the stimulus onset.

Then, to correct for motion artifacts, eliminate periods during which a signal change exceeding ±150 µV was recorded at any of the electrodes—not just the one collecting data from an anatomical site of interest.

Afterwards, for each electrode, average the EEG data collected from all baseline image trials to produce an ERP waveform. Similarly, average the data for oddball trials.

To analyze the data, display the ERP averages from the Pz recording site for both the green target and red control shapes. For the parietal P300 components, assess the amplitude—the height of the component above the baseline value of 0 µV—and its latency—how long it appears in ms after the participant views the circle.

Then, for these peak amplitudes and latencies, use F-tests to determine whether there is a difference between baseline and oddball stimuli.

Notice that for green oddball shapes, the trace peaked at approximately 350 ms after the onset of the stimulus, whereas no P300 peak was observed when the participant viewed the control red target circles.

Collectively, these data suggest that activity in the parietal lobe increases when oddball stimuli are presented, reflecting the neural processes that identify task-relevant, salient stimuli.

Now that you know how researchers use the visual oddball paradigm in sensory information processing, let’s take a look at how scientists are applying this technique to analyze ERPs in other areas.

Although we’ve focused on ERPs produced by healthy brains, some researchers are using the oddball paradigm to understand how concussions—injuries resulting from trauma to the head—affect cognitive processes.

For example, evidence exists that students who suffered a concussion—and who exhibit symptoms such as dizziness or confusion—produce significantly lower P300 peaks when they view a rare oddball image, compared to uninjured control participants.

This suggests that concussions may negatively affect how the brain responds to, and processes, potentially important sensory information.

Other researchers have used a modification of the oddball paradigm—one involving unexpected sounds, rather than images—to better understand the differences between top-down and bottom-up attention.

By studying ERPs produced by oddball tones, scientists have determined that, not only is the P300 peak also enhanced by rare sounds, but that this component can consist of two subparts: an early portion called P3a, and a later P3b element.

Interestingly, these two peaks are observed in the ERPs of participants given the goal of identifying rare sound stimuli. However, only P3a occurs in the waveforms of participants told to just passively listen to sounds, and not given a goal to identify odd ones.

Thus, P3a is thought to deal with bottom-up attention—and how the brain responds to novel stimuli—whereas P3b likely reflects top down attention, and how the brain cognitively classifies targets.

You’ve just watched JoVE’s video on using the oddball paradigm to investigate the processing of sensory stimuli—particularly in the parietal lobe. By now, you should know how to design different stimuli, record EEGs, as well as generate and analyze ERPs. You should also have an understanding of how ERPs can provide insight into cognitive processes, and be used to better understand certain injuries.

Thanks for watching!