Mind-Based Vs. Task-Based Neuroimaging

A BCI device user controls it via his or her brain signal. The EEG (or other neuroimaging) signal is analyzed, processed, decoded, and classified. The end result is an intended movement.

But, what controls the user’s brain signal? Some might say task determines signal: its location, frequency, amplitude and other characteristics.

I argue task is a secondary variable. The primary variable affecting the brain signal is the mind. Brain activity IS of course influenced heavily by task. But it’s also affected by the environment, measurement situation, recent life events (good and bad) and other life context. All of these variables affect the mind, and corresponding brain signal.

The user’s state of mind — perception, recognition, meaning, thought, emotion, language, goals, imagination, intention etc. — is affected by many things. The brain signal thus reflects the mind primarily, task secondarily.

If a user’s mental processes are activated optimally, and the brain signal processed and classified accordingly, the desired action will occur. Mind Target Hit → Functional Neural Network Activity → Brain Signal → Processing & Classification → (Desired) External Action.

For example, if a user’s mind is dominated by a “move the cursor to the left” intention, the corresponding functional neural network activity and brain signal will be classified as “move cursor left,” triggering that action.

What if the mind could be defined more accurately, and more completely? This would allow more accurate brain signal labeling or classification. Better mind definitions enable more accurate, precise, and comprehensive classification of these signals.

More importantly, a group could use more optimally-define the signals they are interested in in the first place. In other words, they could define better brain signal “targets.” The entire team — BCI designer, tester, trainer, and user — could use these to improve their performance. For example for the user, the targets would be more clear, precise, and personalized; desirable for the user to strive toward, easier to hit (strongly and consistently), and adjusted for specific movements, situations, and other context.                                                                                                        

The current cognitive neuroscience framework, despite the best efforts of professionals more skilled and knowledgeable than myself, is very limiting when applied to BCI development and use. Working within it yields vague and inaccurate brain signal targets. There is no one’s fault. Brain science knowledge and skills are invaluable. The problem is they are being applied within the wrong (cognitive neuroscience i.e. mind/brain) paradigm.

Current mind brain targets for BCI control are either ill-defined, or too task-focused. A target might be “move the cursor left” intention (not a bad start, but very incomplete), or “attend to and do whatever you did before to make that action happen” (vague and ill-defined). Or, the target might be 100% task-based, such as “whatever the brain does when the user performs movement X, under conditions Y and Z.”

The reason task-based targets are sub-optimal is because they are much less strongly correlated with the brain signal than the mind. A given state of mind includes not only task influences, but those of environment, situation, recent life history, stage of learning, and other context.

Contrast brain signal labeling based on task with labeling based on the mind, defined as a set of general memories. For instance, the intention “move the cursor left” will include the memories “cursor,” “a computer screen,” and “move left.” This intention — a general memory in its own right – is itself comprised of general memories. These are mainly visual and somatosensory. Among these are “seeing an object move left,” and “the feeling of my right hand & mouse as it moves left.”

The above memories have strong associations as well. These include visuosomatosensory attention (“focus on the cursor”), visual imaging (“imagine it will move left”), and emotion (“feeling calm and relaxed”).

Why label the brain signal based on task, when it can be more accurately labeled based on mind? In fact, I argue it’s possible to define a memory set — its components and associations — for any (common) movement & its context. Movement context would include the person, occupation, lifestyle, movement situation (environmental, social, work/home/lab…), and stage of learning (beginner/intermediate/advanced).

Overall, neuroimaging and brain mapping based on the mind, not the task, has the potential to greatly enhance BCI projects. Mind-based neuroimaging is an effective tool for BCI development and performance — both in the lab and the real world.

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