Download EEG Brain Dynamics

ELECTROENCEPHALOGRAHIC
BRAIN DYNAMICS FOLLOWING
MANUALLY RESPONDED VISUAL
TARGETS
SCOTT MAKEIG, ARNAUD DELORME, MARISSA
WESTERFIELD, TZYY-PING JUNG, JEANNE TOWNSEND
JAMIE PACE
BIOLOGY 1615
INTRODUCTION
When your brain is awake, it is functioning through brain processes across the entirety
of the brain, this facilitates a human’s actions and perceptions. In the study of
Electroencephalographic Brain Dynamics Following Manually Responded Visual Targets, they
documented the brain fluctuation of continuing electroencephalographic (EEG) activity, which
they have defined as, “activity recorded in the human scalp differ markedly with state of
attention and intention. (Makeig and Inlow 1993)
They hypothesized the effects on EEG signals emerge out of a flat baseline, as in the
normal averaged event related potential (ERP). It is known that from anywhere from 50 to 150
ms stimulus information is already greatly distributed throughout the brain. Concluding, there
must be ERP appearance in more than a single brain area.
RESULTS
The independent component analysis (ICA) method was used to experiment on the
subjects. ICA is a process which provides a decomposition of EEG data. In the first task, five
black boxes where displayed across the screen. The subject’s objective was to press a button as
promptly as possible when the dot appeared in a box, which were displayed in a randomized
order. They then recorded response time (RT). Statistics showed that 95% of subjects
responded within a window of time of 150-1000ms and the average RT showed to be 352 ms.
Charts of the subjects average brain reaction time where recorded and displayed.
Where frequency (Hz) was analyzed with time (ms), a color scale in which higher concentrations
of red indicated brain stimulus, and a solid vertical line corresponding to the moment of motor
response. ICA tested single trials on each subject, which were then decomposed into sets of
scalp maps. Black traces (Pz) are simply the observed data. From the data gathered via scalp
maps, the component IC1 was highest in EEG variance.
Component cluster dynamics were evaluated to show the mean scalp map, responselocked ERP image, brain activity, and ERSP, which were then converted into nine graph groups
based on feature. Groups were sorted by frontal and parietal collections, then further sorted by
direction (i.e. left, central, and right). Each cluster details each blink, eye movement, and ERP.
This data revealed that scalp potential was regularly peaking 39 ms before the button press.
Collectively, the nine clusters explained 91.1% of the variance in the ERP total average.
Three wave/peaks were extracted from this data. Posterior positive peaks in ERP’s of both mu
collections, a central collection ERP slow wave, negative frontal midline (FM) collection peak. All
three interactions were detected to occur simultaneously approximately 100 ms after P3f peak.
They concluded to eliminate the possibility phase links in post response EEG activity.
DISSCUSION
Cluster localization, ERSP’s, ERP influence, and functional significance are not entirely
independent of each other, but individually dependent. Studied observations reflect
importance of brain stem systems through ICA gatherings. Since the response was evoked and
time-locked following motor response, positivity was a late complex in many brain areas.
Results of event-related brain dynamics confirm informational association between the
brains cognitive process and macroscopic passage, through EEG data. This information should
boost interest of neuroscientists as EEG dynamic models achieve hemodynamic observations
and expand multi-neuron recordings.
MATERIALS AND METHODS
Subjects were shown five boxes consistently displayed on a screen. Each box was exactly the
same size as the others and they were displayed in a horizontal line across the screen. Then, in a
randomized order, dots would fill a box and subjects were asked to press a button as quickly as possible
preceding the dot. They each had a 76 second block of trials. Thirty segments of the trial were recorded
from every person. Tested subjects were all right- handed with perfect eye vison all between the ages of
19 and 53. They pressed their thumb button as promptly as possible following visual stimuli (i.e. the
green dot). Scalp electrodes (29) were mounted to an electrode cap and the subjects scalp and data was
collected from there. Electrodes were placed beneath the subject’s right eye and left temple and
charged to 512 Hz. A subject’s response was only evaluated if they responded with in the allotted time
(150-1000 ms).
In order to examine response changes and subject stimulus, results from the EEG data was
calculated to ERSP transformations. To exhibit data, they used binomial statistics where p<0.01 at a time
and frequency point. To analyze relationship between the presences of different stimuli, they performed
event related phase coherence. The results were equivalent to that of dipole modeling. The scalp
created a patch of electrical potential which has the same geometry to that of a dipolar element. Two of
these patches connected through the subcortical drive. Lastly, all trials were compiled together and
viewed in a three dimensional animated display.