Transcript Sample spoken presentation - CogSci @ UC Merced

Emotiv as an Affordable Means of Extracting
Recurrent Brain States
Graham Thompson
Bryan Kerster &
Rick Dale
Cognitive and Information Sciences
University 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 microworkshop 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
Rick1 – saw
first segment
Rick2 – saw
second segment
• EEG data was recorded
synchronously during the
viewing of each clip (add
in still from red balloon)
(Hasson et al, 2004)
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
Within subjects correlation
same-segment, different
viewing
Between subjects correlation
same-segment, same viewing
Eric1 – saw first
segment
Eric2 – saw
second segment
Between subjects correlation
different-segment, same viewing
What Does the Signal Look Like?
Three Example Electrodes
Cross-correlation with
EEG Signals
Do 100 times for each pair of
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 crosscorrelation.
Sweet result
may resemble:
r
0
lag
Run paired t-test comparing
same-window vs. anotherwindow (df = 99). Set α for t-test
to .001. (Makes the obvious false
assumption of independence of
lags, for now…)
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?
Cross-correlations
between channels of
a subject .
(red line is
randomized base)
(* = p < .001)
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