I had a project in mind that was waiting for something like this! :)

https://youtu.be/r6sGWTCMz2k

Anyone who has taught piano for example knows the most common mistake of novice students is to omit sharp or flat notes (the black notes) when learning notated music which begins to include them. In this case, the student will practice the wrong notes for long enough before their next lesson that the wrong notes become engrained in their memory model, resurfacing under duress such as in recital. There are similarities for other instruments (strings: intonation, woodwinds: embouchure, percussion: rhythmic accuracy, etc.)

The most talented students seem to gravitate consistently towards robust memory models for their respective instruments technique as a way of freeing themselves up as quickly as possible for the more enjoyable aspects of perfecting a piece of music: refining expression.

Perhaps one day there will be tools which can assist those less naturally predisposed to developing robust memory models, before it's too late for their brain, the way the most talented students do.

What desktops and laptops afforded that mobile takes away, 8 usable fingers aside, is the factor of dedicated computer use (reduced context switching with non-mobile), providing a much better opportunity to keep predominant brainwave patterns away from the "fight or flight" state historically associated to rapid context switching.

Therefore there is one categorical problem (excessive computer use) that is indeed shared across mobile and non-mobile computational platforms alike, and we can point to the people who used their desktops or laptops so much that it could be considered unhealthy, all well before the mobile revolution.

At the same time, the modern epidemic exacerbates the problem by not only summing total computer time between mobile and non-mobile, but there is added the additional factor or rapid context switching which is nearly unavoidable with mobile platforms.

If that wasn't enough, there is also evidence that these newer behavioral patterns are bleeding back from mobile into non-mobile computing, meaning that people are now using desktop/laptops as though they were mobile platforms, rapidly context switching when 10+ years ago they simply did not do this.

Altogether, the evidence indicates that you are right overall, the smartphone was a catalyst to a change in how the internet is interacted with which is the real problem by and large, but conversely, we might be able to use both mobile and non-mobile platforms in a way which minimizes context switching and in so doing restores healthy beta brainwaves rather than encouraging the unhealthy "fight or flight" patterns indicative of this modern (first world) epidemic.

Remote: Yes

Willing to relocate: Yes

Technologies: C#, Java, Python (scientific), C++, Unity, Unreal Engine, Computer Graphics, Digital Audio/DSP, Virtual Reality, Augmented Reality, Android

Résumé/CV: https://www.linkedin.com/in/kieran-coulter-a8248153

Email: kcoulter.dts@gmail.com

On one hand, I somehow feel it's appropriate that an open online course limit itself to methods that are accessible outside of medical research labs and hospitals.

On the other hand, I agree completely that someone could walk away after taking this course, never understanding that they would be dealing with a quality of data of considerably lower fidelity, to the point where failing to take that variable into account could easily lead to false conclusions.

Maybe this is why part of me is "glad" I cracked my head open at a young age and still have a significant gap there in the skull bone - I can get higher amplitude signal placing an electrode there than anywhere else on my head!

This was what I was referring to above, seemingly the most hacker friendly EEG of them all, and shipping in January: http://www.openbci.com/

My research indicated that monaural and isochronic patterns are more effective than binaural.

However, if binaural beats were synchronized with optic driving (an audio pulse arrives in the given ear at the same moment a photic pulse arrives at the corresponding eye), then this kind of integrated approach could certainly trump them both (and simple optic driving as well).

On that note, I would have to say I was a bit disappointed by the Neurosky Mindwave Mobile unit I received - despite being able to bypass their simplified attention/meditation/blinking reduction of the raw input signals and capture the {delta, theta, ..., gamma} filtered bands for further processing, many people (myself included) complained about the apparently low quality of the data, specifically showing large amounts of delta band activity and little else. I resigned that the low-cost interface was simplified to the point where it was a novelty and little else.

Now I am narrowing it down to OpenBCI vs. Muse vs Emotiv. Picking the right one for the handful of projects I want to use an EEG for is proving to be difficult. I'm simultaneously attracted to the ability to take matters more into my own hands with OpenBCI, and the ability to just get started right away with a product like Muse or EPOC.

I'm curious if you were planning to use the Rift for photic entrainment. I haven't seen anyone else intending to get into photic stimulation with the Rift besides a project or two that never seemed to take off like Ocunaut, so if you do plan to, it would be great to collaborate somehow.

Some research has indicated that photic entrainment might be even more effective than the various kinds of aural entrainment (binaural, monaural, isochronic).

http://www.mindalive.com/articleone.htm (1/3rd of the way down, Frederick, Lubar, Rasey, Brim, & Blackburn, 1999)

My impressions from that study are that eyes-closed photic-only worked best for two reasons:

1. Closing the eyelids blocks out extraneous light which reduces interference. 2. No one knew how to properly combine the entrainment modalities yet.

However I believe that if a proper theoretical model is applied, AVE techniques might then become more effective, perhaps even more so if tactile audio were involved as well. http://en.wikipedia.org/wiki/Audio-visual_entrainment http://en.wikipedia.org/wiki/Tactile_sound

To me, a unit like the DK1 is not really usable for anything besides this sort of thing. After all, panning anywhere nearly as quickly as would be needed in a game on a DK1 would get most nauseated fairly quickly. (The DK2 is much better in this regard, and Crystal Cove hopefully even more so)

But the one saving grace for the DK1 was things done very slowly and deliberately, like a relaxed exploration of the Tuscany demo or something like this: http://guidedmeditationvr.com/

During my CS degree I wrote one paper with numerous citations from the field of neuroscience, as I was trying to make a case for ways to change the way we teach and learn so as to build more robust memory models of the things we are trying to memorize. The case I used in my paper was pieces of notated sheet music, but I believe the same principles could hold in areas like language learning (whether computer languages or human) or mathematics equally well.

I'd like to build/buy a good enough EEG to show that specific patterns emerge when we achieve the specific kind of focus that allows for this optimally efficient kind of learning to take place. (The implication being that if we are able to induce this type of brainwave pattern rather than expect the individual to achieve it on their own, then we might be able to make a significant step forward in the field of educational neuroscience).

http://en.wikipedia.org/wiki/Educational_neuroscience

Busted though, reading this specifically to review for a final CS exam in hardware/OSes.

This book might pair nicely with a current Coursera (which, yes, I'm also using to review for the final): https://www.coursera.org/course/hwswinterface