ARC Journal of Neuroscience Volume 3, Issue 3 2018, PP 6-9 ISSN 2456-057X DOI: http://dx.doi.org/10.20431/2456-057X.0303002 www.arcjournals.org ARC Journal of Neuroscience Page|6 Complexity Based Analysis of the Correlation between External Stimuli and Bio Signals Hamidreza Namazi* 167 Division Ave Brooklym, New York 11211, USA In order to correlate different bio signals to external stimuli we can benefit from complexity concept. The complexity can be defined in case of different phenomena in different forms. Therefore, we should be able to quantify different external stimuli using complexity concept. On the other hand, we can also apply complexity concept to different bio signals [1]. In this research, we employ fractal theory to quantify the complexity in case external stimuli (signals or patterns) and different bio signals. Fractals are self-similar objects that show repeating patterns [2] at every scale inside themselves. The self-similarity is quantified using fractal exponent. Fractals can be simple or complex. The computed fractal dimension for a fractal process changes based on the nature of process. In case of simple fractals, the computed value for fractal dimension is integer, whereas the computed value for complex fractal systems is non-integer [3]. Fractal theory has been applied widely to different types of bio signals and patterns to investigate their complex structures. The reported works that analyzed Electroencephalogram (EEG) signal [4-10], respiration signal [11-12], s-ABR signal [13-14], human face pattern [15], heart rate signal [16], eye movement [17-19], human DNA time series [20-23], human gait [24], Magneto encephalography (MEG) [25], spider brain signal [26-27], and animal movement behavior in foraging [28] using fractal theory can be called as some examples in this area. In case that we deal with signal or pattern as external stimuli, we can apply fractal theory to quantify its complexity. For instance, auditory stimuli in the form of music are time series (signals) that can be quantified using fractal dimension. As another example, the complexity of images as visual stimuli can be quantified using fractal dimension. However, we have different types of external stimuli, and not all of them are defined in the form of signal (such as music) or pattern (such as image). In this case, we can employ other types of complexity. For instance, in case of olfactory stimuli, we can use molecular complexity concept to define the complexity of molecular structure of olfactory stimulus. Therefore, by referring to different concepts, we are able to define the complexity of external stimuli. Abstract: Analysis of human reaction to different types of external stimuli is one of the major issues in physiological research. The reactions of human body has a broad range of categories such as brain and heart reactions. In this way, besides investigating about the human reaction, linking between characteristics of external stimuli and human reaction is a very important issue. Besides employing all developed methods for analysis of external stimuli and human reaction, none of them could make the relation between the characteristics of external stimuli and human reaction. Fractal theory is a new mathematical approach that defines the complexity of processes. Since external stimuli (in major) and human bio signals can be quantified using fractal theory, in this editorial paper, we discuss about employing fractal theory to make links between the external stimuli and human bio signals. In order words, we discuss about an approach that can correlate the complexity of external stimuli and the complexity of different bio signals. In fact, this investigation is quite important as it not only analyzes the human reaction to external stimuli, but also correlates the characteristics of human reactions to external stimuli. The application of this analysis could be widely considered in different areas of research works related to biomedical engineering. Keywords: Human reaction, External stimuli, Bio signal, Fractal, Complexity. *Corresponding Author: Hamidreza Namazi , 167 Division Ave Brooklym, New York 11211, USA, Email: hrnneuromap@gmail.com