Acknowledgements

The human brain consumes 106 times less energy than the currently fastest super computer [1], while maintain-ing a comparable performance in many demanding tasks [2]. This energetic efficiency has been suggested to result from primitive computations on a molecular level [3]. However, while the importance of ion channels on energy efficiency has been the primary focus of research [4,5], most computations occur at the molecular level prior to the amplification step and prior to the informa-tion transmission through neurons. We calculate the amount of energy consumed by such computations and compare their structural and functional properties. As a starting point, we chose 2000 reactions in the signaling pathways of CA1 hippocampal neurons [6]. As not every reaction consumes either one or zero ATPs, we undergo a wide literature search to identify the exact energy con-sumption of over 60 million of possible feedback loops. We find that the number of ATPs consumed is related with size of positive feedback loop. Hence, this study provides the first systematic and detailed attempt to inves-tigate the energy consumption of information-storing primitive computations and points towards energy effi-cient motifs for synthetic biology