BCI Brain Signal Targets: Part 3

In Parts 1 and 2 I have argued that (a) the mind controls the brain signal, (b) the mind is mostly a set of general memories, based on experience (not processing), and therefore (c) general memories are optimal mind/brain “targets” for designer, teacher, learner, and user to shoot for.

In other words, BCI brain signal targets are optimally defined as a set of general memories.

How would one build an optimal mind, or more specifically general memory, BCI target? A movement intention is a good starting point. For example, consider a “cursor moves left” intention. It would be comprised of a memory set featuring “cursor,” “left,” and “cursor moves left.” These are perceptual 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. These memories are definable. They have a particular range of perceptual content; as well as cognitive, emotional and other associations. Once this memory set is acknowledged and listed, it can then be connected and weighted.

It’s important to realize all human memory has content. Can the reader think of a memory that does not have definable content? By definition, a memory set has content that can be summarized, if not fully defined.

Once the target 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 general memories make the best BCI brain signal targets be useful? Because, it leads to mind and brain signatures of any (common and desired) movements, within any context. These signatures would be more accurate, comprehensive, and precise than task-based signatures or other cognitive neuroscience conceptualizations. They can be fit to the person, situation, task, and other context.

The basic idea is to recognize user “state of mind” exists, it occurs in the brain, it can be defined as a set of active general memories (based on past experience), is represented physically by a corresponding set of brain signal range activity, their variability across movements and context can be defined, and these mind/brain signal ranges make ideal BCI targets for the designer, trainer, learner, and user to strive to “hit.”

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