About this Research Topic
The term neural computation and computational theory of cognition comes from the assumption that neural activity can be computed and that neural computation can explain cognition. With this assumption the brain could be considered as the hardware and the mind the software. This means that hardware would be the set of cells that make up the brain and the software the way in which the neural networks are functionally formed. Following this model, the following question arises: what are the computational rules by which neural networks operate in the brain?
If we consider for a moment that the human brain is a kind of machine, to measure the reality of the world, the natural question that arises is whether there is a metric with which that reality is measured, and if so, what is that metric? In addition, is there any fundamental unit that the brain uses to categorize the attributes of the energy with which it interacts, and thus performing many trillions of calculations per unit of time that allow the neural functionality? Concepts from physics, if feasible, might be introduced in the area of neurosciences. If invariant quantities that would allow the establishment of conservation laws in the brain were found, a mathematical theory that would describe the biological functioning of the brain could be generated. On the other hand, non-conserved quantities such as the variability in the brains' responses to a constant external stimulus could indicate a concealment of an abstract symmetry in the magnitude of the response.
The goal of the current Research Topic is to investigate neural network oscillations, while searching for a unifying theoretical framework to better understand mechanisms of control that underlie the processes such as sensation, perception, attention, motor control, memory, and consciousness.
The research Topic welcomes original manuscripts as well as reviews focused on but not limited to the Brain Network Physiology including following themes:
•Analogue and digital computations in artificial neural networks
•Neural communication and Information exchange in the human brain
•Single neuron computations - gain function, spike trains, firing rate, depolarization block
•Phase and amplitude relations between rhythmic activities within and between neural assemblies
Lastly, a noteworthy Research Topic that we would like to highlight is "The New Frontier of Network Physiology: From Temporal Dynamics to the Synchronization and Principles of Integration in Networks of Physiological Systems" published in Frontiers in Network Physiology.
Link for it: https://www.frontiersin.org/research-topics/10298/the-new-frontier-of-network-physiology-from-temporal-dynamics-to-the-synchronization-and-principles
Important Note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.