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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.