Before revision:  With the help of functional networks, neural decoding, and deep learning based MVPA analysis of individual cognitive component, we arrived at the conclusion that mere affect is unable to provide varieties of emotions unless coupled with cortical cognitive meaning making mechanisms.
After revision:  With the help of functional networks, neural decoding, and deep learning based MVPA analysis of individual cognitive component, we arrived at the conclusion that mere affect is unable to provide varieties of emotions unless coupled with cortical cognitive functions such as autobiographical memory, dmn, self-referential, social, tom and salient event detection. Our model suggests three testable hypotheses. First, affect and physiological sensations alone are inconsequential in defining or classifying emotions until integrated with the domain-general cognitive systems. Second, cognition and affect modulate each other throughout the generation of meaningful instance situated in the current context. And, finally, the structural and temporal hierarchy in URLanization and anatomical projections plays an important role in emotion responses in terms of physiological activities and their duration.