PSYC 410 EEG/ERP Project

Today we will conclude our three-part lab exercise concerned with EEG and ERP recording and analysis. You will analyze the EEG/ERP data collected during various EEG sessions.

This EEG/ERP report is due on Wednesday May 13^rd @ 11:55 pm

See below for specific instructions on how to submit.

This assignment will be very similar to the lab reports you've done throughout the semester. The primary difference is that I will not furnish you with a step-by-step guide for carrying out the analyses.

As was the case for the fMRI project, you are allowed to use any resource you'd like, including our lab wikis, to assist you in your analyses. This also means you are permitted to ask each other for assistance. However, you are not permitted to work together. That is, asking for a little help here and there when you get really stuck with something is fine, but I expect you to primarily work independently.

What do I mean when I say you can each other for a “little help”, but that you are not permitted to work together?

Pretend your classmates are professional colleagues with whom you have a friendly relationship. You would definitely not hesitate to reach out to such a colleague if you hit a brick wall and needed some advice. But you certainly would not fill up their inbox and expect them to hold your hand through your analysis.

Go Slow. Be Methodical. Redux

Go Slow. Be Methodical. The same warning I gave you for your fMRI project equally applies here. Go Slow. Be Methodical.

Go Slow. Be Methodical. Setting up analyses can be repetitive and tedious, so it's only natural to want to breeze through it. But you must fight the temptation to just click-click-click-Go. I can't begin to count the many dozens of hours I've spent re-doing analyses because I was hasty and careless the first time. Think about each setting as you set it. Make sure you understand why you're using it, and that you're setting it correctly. Go Slow. Be Methodical.

Readings to be completed prior to this lab:

Readings to be completed prior to next week's lab:

There is no next week!

Housekeeping

1. Rename the old EEG directories. In Terminal:

mv ~/Desktop/input/eeg/N170 ~/Desktop/input/eeg/N170_old1

2. Download the data for lab EEG Project.

Make sure the downloaded file N170.zip is on your Desktop. If not, move it there.
Double click the file to unzip it.

3. Move the data directory. In Terminal:

mv ~/Desktop/N170 ~/Desktop/input/eeg/

Turning in your assignment

EEG Report: Turn in your report via Moodle.
EEG Analysis: Turn in your data analysis on your by following the instructions below.

1. Save all output into the '~/Desktop/input/eeg/N170 directory

2.. Once you have completed the project, create a zipped copy of the N170 directory and move it to your Desktop.

Highlight the N170 directory in the Finder window.
Select File –> Compress “N170”.
- This will create N170.zip
Upload N170.zip to the Google folder that you shared with me for your fMRI project
- You do not need to change the name of the folder. You can leave it named yourlastname_410_fMRI, and I will just look for N170.zip folder inside.

Remember: this is only to be done once you are entirely done with the analysis portion of your project.

N170 Paradigm

The Gist

The N170 is a large negative deflection that is maximal over right occipitotemporal scalp (for example, electrodes P10 and P08). The deflection is observed in response to most visual stimuli, but the amplitude of the response is significantly larger to faces than to all other stimuli. Because of this amplitude difference, it is thought that the N170 reflects the activation of “face selective” neurons. That is, neural populations that are tuned to prefer faces to all other visual stimuli.

You can learn more about the N170 here,here, and here.

Data Used for This Project

Participants

3 participants
All right-handed
Mean age 20.6

Task Description

In this experiment, participants viewed images from one of four possible categories: faces, greebles, tools, and targets (see examples below). The participant was asked to press a button as quickly as possible whenever they saw a target (a large colored circle). The images appeared every 1800-2200 ms in random order. The study was designed so that there were 60 trials each for the faces, greebles, and tools categories, and 20 trials for targets (200 trials in total).

Because there were so few target trials (and thus low SNR) and because they are not an important control stimulus, you probably don't want to plot them in your figures.

Task Parameters

The data for this section of the lab were acquired at Kenyon using the BioSemi ActiveTwo system. EEG was acquired at a sampling rate of 2048 Hz from 64 scalp electrodes arranged in the 10/20 system. Data was digitized with 24-bit resolution. After acquisition, the data were downsampled from 2048 to 256 Hz.

Event Marker Codes

Code	Condition
1	Faces
2	Greebles
4	Tools
8	Targetrs

Notice that the event codes are 1,2,4,8, rather than 1 to 4. Keep this in mind when you create your eventlists, and remember that event codes are not the same as bin codes.

Analysis

Preprocess the EEG data (you can skip doing artifact rejection for the purposes of this small analysis/report)
- Rereference to the average reference
- Apply a 4th order IIR Butterworth bandpass filter of .01 - 30 Hz
Create ERPs and scalp topographies for the three participants
Create a grand-average ERP and scalp topography

Think carefully about how you want to create your topography. Remember, you want to set your parameters to best highlight any observed effect.

EEG/ERP Report

Your lab report should be written in the format of a brief journal article, which includes the following sections.

Introduction

Brief description of the N170 phenomenon. This can be just a paragraph or so.

Here are a couple of papers describing the ERP:

Methods

A description of the task paradigm.
The number of participants (i.e., sample size)
A description of the EEG parameters (e.g. sampling rate, ADC conversion, bandpass parameters, number of electrodes, etc.)
As with lab 09, you are not expected to know all of the info you'd find in a published paper, but be sure to report all the info you have.
Include plain language descriptions of what you did and why you did it.
- Of course, this is not something that would would be found in a “real” paper

Things to keep in mind when you do your analysis…

Do not blindly use the same values that you used for the CNV study. For instance, the N170 is a fast ERP that is complete after a few hundred milliseconds. So do you think you'd want to create epochs that go all the way out to 3000 ms?

Results

A summary of your main findings with figures (see list of considerations below)
At minimum, include the following figures to demonstrate your results
- Time-voltage plots (i.e., ERPs) illustrating the major experimental comparisons for your experiment
  - Include at least one difference wave
- Topographic maps illustrative of the major experimental effects.
- Your primary figures should be of the group average, but it is often useful to include an example from a single subject as well.

I do not expect any statistical analysis of your data (i.e., if the difference looks real, then we will accept it to be real. Sadly, this approach does not work in real life).

I do expect to see polished and attractive figures with legends.

When you create your topgographic maps, you'll want to make sure outside is selected in the Map type section (if you're creating a 2D plot). This will ensure that relevant electrodes like P10 are displayed.

Discussion

Briefly discuss your results with regard to the task (this can be a simple paragraph or two)
If you were the first person to run a face perception ERP study, what would you conclude? What did you learn about visual processing of faces compared to other objects? The time frame of face processing? Etc.

References If you cite any work in your paper, be sure to include an APA style reference section.

Your report should consider the following:

Identify the experimental effects in your ERP waveforms.
- Do you have a a face effect?
  - What conditions should be compared to evaluate these effects?
- Is the effect consistent across subjects?
  - Look at one or more individual subjects, and also at the across-subject (group) summary data
- When does this effect occur in time?
  - What is the latency in ms of your main effect?
- What is the scalp distribution of this effect?
  - Map the scalp topography.

Even though you are not writing a full intro and discussion, I would still like you to use the template manuscriptI suppled for the fMRI project (but ignore the minimum word counts in that document).

This is the “Mini-Empirical Paper EEG/ERP” assignment on Moodle.

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