Emotiv as an Affordable Means of Extracting Recurrent Brain States

Graham ThompsonBryan Kerster &Rick Dale

Cognitive and Information SciencesUniversity of California, Merced

The Price of Dynamic Brain Measures

•Conventional EEG and other brain recording hardware are expensive

• Few labs can afford them

•So dynamic brain measures are not often used

Purpose: Explore one technology that could make brain measures more accessible

•New technology is starting to bring down prices and make brain recording accessible

•The Emotiv EEG is the first consumer grade electroencephalography system

•This talk will serve as a kind of micro-workshop detailing our experiences with the Emotiv EEG as researchers interested in complex systems and new technology.

Emotiv Headset•14 Channel EEG

•Designed for gaming, •consumer biofeedback

•Affordable–$300 basic headset–$750 research edition

•Wireless, highly portable

Some Important Things they Tell you about the Hardware

• Includes gyro output (captures head movements)

• Samples at 128 Hz from a 2048Hz internal rate

• Records voltage from easy to use saline sponge sensors

• SDKs available in C++ & Python (unsupported)

• Can send data to any windows device with usb capability (desktop, laptop, tablet etc. )

Some Important Things they Don’t Tell you about the Hardware

• Hair is a huge issue for getting a good connection with the saline sensors.

• When batteries are low the sensors will continue operating but start returning increasingly random data (always keep charged)

• For some reason you can’t record while the device is plugged in

• Saline + exposed metal parts = corrosion

Is this “Real” EEG?

Badcock et al. (2013) Validation of the Emotiv EPOC® EEG gaming system for measuring research quality auditory ERPs. PeerJ 1:e38

http://dx.doi.org/10.7717/peerj.38

- Emotiv was found to be equivalent to a research grade system (Neuroscan) for recording auditory ERPs.

Ekanayake, H. (2010). P300 and Emotiv EPOC: does Emotiv EPOC capture real EEG.

- Emotiv could reliably pull out P300 erp (oddball paradigm) responses though not as cleanly as a research system.

Test Case: Using The Emotiv for Studying Neural Synchronization

• Volunteers watched two film segments from a French film (the red balloon)

• Each segment was viewed twice

• EEG data was recorded synchronously during the viewing of each clip (add in still from red balloon)

(Hasson et al, 2004)

Rick1 – saw first segment

Rick2 – saw second segment

Eric1 – saw first segment

Eric2 – saw second segment

Test Case: Using The Emotiv for Studying Neural Synchronization

Are there correlations between the brain signals of people who watched the same clip?

Rick1 – saw first segment

Rick2 – saw second segment

Eric1 – saw first segment

Eric2 – saw second segment

Between subjects correlation same-segment, same viewing

Within subjects correlation same-segment, different viewing

Between subjects correlation different-segment, same viewing

What Does the Signal Look Like?Three Example Electrodes

Cross-correlation with EEG Signals

1. Choose a window size of approximately 25 seconds (3k data points) at the same time within each of 2 channels.

2. Run a cross-correlation from lag -15s to +15s.

3. Choose a random window from another point in one EEG signal; do the same cross-correlation.

Do 100 times for each pair of signals

Run paired t-test comparing same-window vs. another-window (df = 99). Set α for t-test to .001. (Makes the obvious false assumption of independence of lags, for now…)

0lag

r

Sweet result may resemble:

Cross-correlations between channels of a subject . (red line is randomized base)

(* = p < .001)

Within a Viewing: Do Electrodes correlate with each other?

Cross-correlations between channels of a subject . (red line is randomized base)

(* = p < .001)

Within Subjects: Do they correlate with themselves on two viewings of the same clip?

Cross-correlations between channels of a subject . (red line is randomized base)

(* = p < .001)

Between Subjects: Do subjects signals correlate with others watching the same clip?

Cross-correlations between channels of a subject . (red line is randomized base)

(* = p < .001)

Between Subjects: Do subjects signals correlate with others watching a different clip?

Conclusions

•There are some reliable correlations within and between the EEG waveforms of subjects watching the same clips

•Emotiv is an effective (and cheap) means for getting dynamic brain measures like these

•Future? Whole brain coherence measures, recurrence analysis, synchrony, entrainment etc….

Thank You