The Penn Electrophysiology of Encoding and Retrieval Study (PEERS) is a multi-session experiment looking at scalp EEG during free recall and recognition. We recruit both younger adults (16-30) and older adults (60-90) for 22 or 9 sessions, respectively.
Please see the information below if you are interested in volunteering for this study.
Information for volunteers
Studying the brain
At the Computational Memory Lab, we use brain recordings to better understand how human memory works. We are devoted to learning how people form and retrieve memories. Eventually, we hope this information will be used to improve the lives of people with brain disorders and restore normal memory function to those who have lost it.
About our tasks
The Penn Electrophysiology of Encoding and Retrieval Study focuses on episodic memory. This is your memory for everyday events (including people, places, and things) in time. Because these memories are unique to each person individually, we must find a controlled way to learn about this form of human memory. In this study, we use lists of words, each individual word representing an "episode" in time. Very simply, we will ask you to study lists of words and then recall them in any order.
What is EEG?
"EEG" stands for electroencephalogram. There are many different types of EEG nets, and you may even have worn one before. The EEG nets we use do not require gel or scalp abrasion. The electrodes are housed above a sponge, which sits on your scalp, that is soaked in an electrolyte solution to allow for good conductivity of your brain's electrical activity. This solution is comprised of baby shampoo (to dissolve the oils on your scalp), distilled water, and potassium chloride (a kind of salt). Although it is rare, some people do experience mild irritation from the solution.
How to get involved
You must meet the following criteria:
- You must be right-handed
- English must be the first language learned to speak
- You must be aged 18-30
- You must be affiliated with a University. This means an undergrad or grad student, a recent graduate, or taking classes over the Summer. (This requirement is stipulated in our NIH grant.)
- You must be able to sit still for up to two hours
Because the study is a total of 22 sessions long, be aware that there is some time commitment involved. Generally we ask that our participants come in at least twice a week over the course of two or three months.
A note: you must be able to take out any ear- or eyebrow-area jewelry you have. Also, some hairstyles may interfere with the net coming in contact with your scalp, such as non-removable braids, dreadlocks, or very thick, long hair. We should be able to tell you if this is an issue as soon as you come in, but if you have any questions about these requirements, feel free to ask.
Contact us at email@example.com or 215-746-0407 to see if we are running sessions for which you may qualify.
Information for researchers
PEERS is an extended experiment consisting of 20 sessions of free recall and recognition memory tasks, followed by 2 sessions of standardized psychometric tests. High-density scalp EEG is recorded during free recall/recognition sessions.
The following publications draw on the PEERS dataset:
- Healey, M. K., Crutchley, P., and Kahana, M. J. Individual differences in memory search and their relation to intelligence. Submitted. (more)
- Healey, M. K. and Kahana, M. J. Is memory search governed by universal principles or idiosyncratic strategies? JEP: General (in press). (more)
- Lohnas, L. J. and Kahana, M. J. Compound cueing in free recall. JEP:LMC (in press). (more)
- Lohnas, L. J. and Kahana, M. J. Parametric effects of word frequency effect in memory for mixed frequency lists. JEP:LMC (in press). (more)
- Miller, J. F., Kahana, M. J., and Weidemann, C. T. (2012). Recall termination in free recall. Memory & Cognition, 40(4), 540–550. (more)
(List is current as of May 2013. See Publications for all lab publications.)
Information will be posted here when the PEERS behavioral and EEG datasets are shared publicly. Please see Data Archive for currently-available datasets.