# IV. Tasks & Monitoring

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**Required PPE: Gloves, Lab Coat**
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***

## EEG Tasks

{% stepper %}
{% step %}

### Run EyesOpenEyesClosed Task

* Open task folder on the participant's PC by selecting the tree icon titled "Session 3"
* Select the EyesOpenEyesClosed Task
* Enter Participant ID
* Guide the participant through the eye tracker calibration&#x20;
* Have the participant complete the task
  * The EEG will automatically start and stop recording on its own
  * Check impedance between task segments

<details>

<summary><strong>EyesOpenEyesClosed Task Timeline ⏱️</strong></summary>

* <mark style="background-color:green;">**Eyes Open:**</mark> 10 min of participant's eyes open
* <mark style="background-color:red;">**Break:**</mark> new instructions presented for next segment
* <mark style="background-color:green;">**Eyes Closed:**</mark> 10 min of participant's eyes closed
* <mark style="background-color:red;">**Task Ends**</mark>

</details>
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{% step %}

### Run Pitch Discrimination Task

* Select "Start a New Study" when prompted at the end of the previous task
* Enter the participant ID: **19XXX**<mark style="color:blue;">**p**</mark> (*<mark style="color:blue;">**p for pitch**</mark>*)

{% hint style="warning" %}
[**Check impedance**](https://app.gitbook.com/o/KxaJPnwXhmNyAW1gWkgG/s/Xc1cErLYtkyOjWlG5P3Z/~/changes/303/study-protocols/muri/muri-session-3/iii.-impedance-check#check-impedance) **before opening or running the task**
{% endhint %}

* Select the Pitch Discrimination Task from the task folder on the participant's PC
* Enter Participant ID
* Guide the participant through the eye tracker calibration&#x20;
* Have the participant complete the task
  * The EEG will automatically start and stop recording on its own
  * Check impedance between task segments

<details>

<summary><strong>Pitch Discrimination Task Timeline ⏱️</strong></summary>

* <mark style="background-color:red;">**Thresholding Practice:**</mark> practice discriminating between 2 tones separated by 500 ms for 5 trials
* <mark style="background-color:green;">**Thresholding Procedure:**</mark> discriminate between 2 tones separated by 500 ms to determine their pitch discrimination threshold in Hz for 64 trials
* <mark style="background-color:red;">**Break:**</mark> new instructions presented for next segment
* <mark style="background-color:red;">**Interval Practice:**</mark> practice discriminating between 2 tones separated by varying intervals for 5 trials
* <mark style="background-color:green;">**Thresholding Procedure**</mark><mark style="background-color:$success;">**:**</mark> discriminate between 2 tones separated by varying intervals to determine their pitch discrimination threshold in Hz for 64 trials
* <mark style="background-color:red;">**Task Ends**</mark>

</details>
{% endstep %}

{% step %}

### Run Duration Discrimination Task

* Select "Start a New Study" when prompted at the end of the previous task
* Enter the participant ID: **19XXX**<mark style="color:blue;">**d**</mark> (*<mark style="color:blue;">**d for duration**</mark>*)

{% hint style="warning" %}
[**Check impedance**](https://app.gitbook.com/o/KxaJPnwXhmNyAW1gWkgG/s/Xc1cErLYtkyOjWlG5P3Z/~/changes/303/study-protocols/muri/muri-session-3/iii.-impedance-check#check-impedance) **before opening or running the task**
{% endhint %}

* Select the Duration Discrimination Task from the task folder on the participant's PC
* Enter Participant ID
* Guide the participant through the eye tracker calibration&#x20;
* Have the participant complete the task
  * The EEG will automatically start and stop recording on its own
  * Check impedance between task segments

<details>

<summary><strong>Duration Discrimination Task Timeline ⏱️</strong></summary>

* <mark style="background-color:red;">**Thresholding Practice:**</mark> practice discriminating between 2 tones separated by 500 ms for 5 trials
* <mark style="background-color:green;">**Thresholding Procedure:**</mark> discriminate between 2 tones separated by 500 ms to determine their duration discrimination threshold in Hz for 64 trials
* <mark style="background-color:red;">**Break:**</mark> new instructions presented for next segment
* <mark style="background-color:red;">**Interval Practice:**</mark> practice discriminating between 2 tones separated by varying time intervals for 5 trials
* <mark style="background-color:green;">**Interval Procedure:**</mark> discriminate between 2 tones separated by varying time intervals to determine their duration discrimination threshold in Hz for 64 trials
* <mark style="background-color:red;">**Task Ends**</mark>

</details>
{% endstep %}

{% step %}

### Close NetStation&#x20;

* Ensure that the EEG has stopped recording
* <mark style="color:blue;">**Close NetStation before disconnecting the net**</mark> by selecting "Quit Net Station and Shut Down Amp"
* Disconnect the net from the amp once NetStation finishes closing
* Put the connector back in its plastic bag before handing it to the participant
  {% endstep %}
  {% endstepper %}

***

## Monitoring EEG

EEG recordings are highly sensitive to various sources of noise and artifacts, which can compromise data quality. Here are some common issues that arise during EEG data collection, how to visually identify them, and best practices for handling them.

<details>

<summary><strong>Participant Movement 🕺</strong></summary>

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**PROBLEM**

Movement artifacts are among the most common sources of noise in EEG. This could stem from a variety of sources such as:

* fidgeting, shifting posture, or speaking can cause sudden jumps in the EEG signal
* large muscle movements (e.g., jaw clenching, head tilts, scratching) introduce high-amplitude distortions
* smaller repetitive movements (foot tapping) can rhythmically distort the signal and add motor cortex artifacts.

Regardless, any sort of movement will always lead to added noise into our signal, which is generally undesirable.
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{% hint style="info" %}
**VISUAL INDICATORS**

Visually, movements can vary in their presentation, depending on their origin. These can include:

* large spikes or sharp deflections in the signal.
* abrupt discontinuities in multiple channels.
* periods of high-frequency noise due to muscle tension.
* a repetitive, wave-like pulse that reflects rhythmic micro-movements such as foot-tapping.

Aside from the EEG's characteristics, you will also always be able to identify movement by the participant moving.
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{% hint style="success" %}
**BEST PRACTICES**

* Encourage participants to remain still and relaxed.
* Ensure proper chair and cushion positioning.
* Provide clear instructions on minimizing movement.
* Note down any large movements undertaken by the participant in the EEG log including time stamps.
  {% endhint %}

</details>

<details>

<summary><strong>Bad Electrodes 💥</strong></summary>

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**PROBLEM**

Some electrodes may carry high noise in their signal **despite low impedance**. This could stem from a variety of reasons including:

* electrode is sitting on a pulsating vein (i.e. picking up heart rate)
* the participant has residual conditioner or sweat in their hair
* the electrode is located in a high-movement area (cheeks/ears/eyes)
* the electrode has reached its demise

Regardless of the reason, bad electrodes are a major barrier in later spatial analysis, if not handled correctly.
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**VISUAL INDICATORS**

Visually, a bad electrode is usually quite obvious. These indicators include:

* the electrode signal line is moving all over the screen
* the electrode has repetitive pattern (heart beat/pulse/breath)
* the electrode is much bolder than the rest

Again, an individual bad electrode will stick out like a sore thumb relative to all others. It is important to note that we might see these patterns across a consecutive set of electrodes as well.
{% endhint %}

{% hint style="success" %}
**BEST PRACTICES**

* If a single electrode is bad, always check the contact of that electrode before anything else.
* Document and flag it for interpolation in the lab manual.
* If you notice an electrode being repeatedly problematic over multiple participants and sessions, notify an supervisor. The electrode may need ot be replaced.
* **Do not include bad channels in ICA**, as indicated in the Cleaning Manual.
  {% endhint %}

</details>

<details>

<summary><strong>Electrical Noise 🔋</strong></summary>

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**PROBLEM**

Electromagnetic interference (EMI) from external sources can introduce periodic or constant noise in EEG recordings. Common sources include:

* Power lines (50/60 Hz noise).
* Electronic devices (phones, monitors, chargers).
* Poor grounding of EEG equipment.

These issues will usually be evident right from the beginning of the recording - after impedances have been checked and fixed.
{% endhint %}

{% hint style="info" %}
**VISUAL INDICATORS**

Electrical noise is usually equally distributed across **ALL** channels, and is a systemic problem.

* A consistent high-frequency oscillation (50/60 Hz).
* Noise present in multiple channels at once.
* Waveform distortion that is synchronized with the power cycle.

In other words, the electrodes will look 64 wavy twins.
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**BEST PRACTICES**

* Keep mobile phones and unnecessary electronics outside of the EEG booth.
* Apply a 60-Hz notch filters in the left panel under 'Filter' to minimize power line interference.
* If all else fails, restart the EEG amp with the help of a supervisor.
  {% endhint %}

</details>
