In my last 2 posts I argue (1) the mind controls the brain signal, and (2) brain signal targets are an expression of corresponding state of mind targets. In this post I will argue that mind/brain targets are more accurately conceptualized as general memory targets.
For example, a “cursor moves left” intention would be comprised of a memory set featuring “cursor,” “left,” and “cursor moves left.” These are general memories comprised of a range of cursor sizes and shapes, left directions (straight left, left but a little up, left and down 1 inch, etc.), and cursor movements.
Whenever the user attempts to move a cursor, a specific memory set will activate each time. These memories have definable perceptual, cognitive, emotional and other content. (Can the reader think of a memory that does not have definable content?). Once listed, the memory set can be connected, weighted, and labeled excitatory or inhibitory.
Once a memory set is defined, a corresponding set of functional neural network (FNN) ranges can be defined as well. And, a corresponding set of brain signal ranges. A general memory set = a set of FNN ranges = a set of brain signal ranges.
Why might the idea a state of mind = a general memory set be so useful? Because, it leads to mind/brain signatures of specific movements that are more accurate, comprehensive, and precise than current cognitive neuroscience conceptualizations. These signatures can also be fit to the person, situation, task, and other context. The basic idea is to recognize “state of mind” is a thing, it exists in the brain, it can be defined as a set of general memories (based on past experience), are represented physically by a corresponding set of brain signal ranges, and these memory/brain signal ranges make ideal BCI targets for the designer, trainer, learner, and user to strive to “hit.”