ABSTRACT Utility of graphical representation of EEG data and colour-maps are now well established. Research on localisation and activity in neuronal pathway are also progressing. The EEG data could be visualized simultaneously as colour-maps and as connected neuronal pathways simultaneously as a movie on a GUI for diagnosis and understanding of the brain activity. The colour-maps are generally constructed using ICA. In this paper, the same is constructed using a compressed sensing technique. A GUI with the connected graph and magnitudes are also generated from EEG. General Terms Color mapping, Compressed Sensing, Connectivity Keywords EEG compressed sensing, colour map, connectivity, GUI. 1. INTRODUCTION The only non-invasive methodology which is involved in measuring the electrical activity of brain is Electroencephalogram. EEG waves under excitement and depression are not regular and not deterministic. As such apart from EEG; the existing functional investigations include fMRI, SPECT, Magneto-encephalography and PET. Each area in the brain is responsible of a particular task, it is necessary to know the area involved for task done, since brain functions can be evaluated using electrical activity of the brain. Locating the functional area in the brain for a particular task is the ultimate aim of this paper. There is functional brain atlases available mainly based on PET and fmRI studies. Main problem with functional brain atlasing is the uniformity of paradigms visualizing the colour map, much information about the brain used for eliciting functional activity and the inconsistency of responses. Brain activity is dynamic and network based. Brain atlases are constructed from the EEG time series data does not render diagnosis but helps in a way to make diagnosis by the clinicians. The same function will have regions of the brain at the specific time instant can be components in different areas with one nodal area or a governor. In order to understand more in detail about the brain functionality, connectivity play a major role in neuroscience. Usage of graph theory [1] is involved in connectivity analysis in case of seizure. Studying the functional connectivity in the brain through a crude test such as EEG especially looking at the daily activity of an individual will be gross generalization. This network regularization is analyzed using coherence and synchronization likelihood [2]. Besides simple potential mapping connectivity provide information to understand more about brain activity. The functional connectivity is estimated using high resolution EEG [3]. Connectivity provides information regarding the connection among the spatially remote regions of the brain, which is of much importance in neuroscience. Visualizing EEG data in the form of colour maps is applied in many of the research to study the activity of the brain. In response to certain medication such as psychotropic medication brain mapping provide information which is used to study the response of the brain. Brain mapping also is used to study the insomnia characteristics. In certain cases the cortical activity and mapping power are compared and coherence and asymmetry measures are also examined. The technique of Brain mapping is useful in many applications, an individual response for a particular medication; understand about emotional responses etc… Functional area with respect to EEG signal been mapped which is responsible for a particular task and the functionality of brain can be studied in detailed through connectivity in this work, but brain mapping is not a substitute for EEG. Christopher Wilke (2008) estimated time-varying connectivity patterns through the use of an adaptive directed transfer function [4], similarly Pieter van Mierlo and colleagues (2009) studied time-variant functional connectivity pattern during an epileptic seizure [5]. Brain is a complex organ, whose functions and responses are still a miracle. These potential studies and connectivity pattern would serve as a limelight to understand the functionalities of brain. Brain colour mapping is a pseudo colour representation to know the region of maximum functionality at a certain instant for a particular human task. This work mainly used by the people to visualize the EEG activity over the scalp to understand the electrical activity on the scalp. Only by activity cannot be obtained, so a work taken up in the area of connectivity to know the areas which functionally connect the other remote areas of the brain. By determining the flow of information the connection or the links between the remote identified.In this paper, colour mapping done with respect to the amplitude of EEG signal via compressed sensing. For the smooth colour map, the data on the electrode locations are not sufficient, hence interpolation is necessary. Those points are involved in producing smooth continuous colour maps. As this colour maps are the outcome of the EEG data on the electrode points, it helps in knowing the areas involved in activity at that particular time. Besides, connectivity using adaptive directed transfer function, which determine the time-variant connectivity pattern by analyzing time-varying
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