I also work in a similar lab as a phd student. Kevinalexbrown's points are spot on. Currently, the main challenges for implementing this clinically are
1) stability of the electrode array over long timescales.
2) increasing the number of degrees of freedom of robust control that we can decode from the neural data. Activity in the motor cortex inherently lives in a (very) roughly 10 dimensional space, which is a bit of a mystery since we use thy activity to control hundreds of muscles independently. What this means, is that when you record from 96 electrodes simultaneously, many of the neurons picked up by the array are correlated, such that the resulting dimensionality is much lower than the number of neurons
3) An important step forward will be to develope optogenetic (or other) sensory write in, using pulses of light to activate neutrons in specific patterns that mimic priprioceptive signals from your limbs. This will increase the speed and robustness of movent via faster closed loop feedback.
4) Processing power. Currently it's typical to run decoders on real-time PC's. Creating an embedded processor capable of sufficiently low power operation with enough processing power to run the decode is non-trivial, especially if you want to implant this in the brain.
It is very unlikely, as suggested elsewhere, that current web tech will impact BMI research at all. The primary interesting tech is in the decode algorithm, which is a modified form of the Kalman filter. There is, however, a lot of room for hackers in research. I recently made the switch from working in defense, building robots and designing sensor fusion algorithms, to a phd in neuroscience. Probably won't pay as well long term, but it's far more rewarding and interesting! I'm surrounded by scientists that need better (software and hardware) tools and analysis methods. Also, an infusion of ideas and values aligned with open access publishing (or changing the scientific publishing model altogether), open source software, data and code sharing, etc. would generally benefit all and accelerate scientific research, but that's another topic worthy of more discussion elsewhere.
1) stability of the electrode array over long timescales.
2) increasing the number of degrees of freedom of robust control that we can decode from the neural data. Activity in the motor cortex inherently lives in a (very) roughly 10 dimensional space, which is a bit of a mystery since we use thy activity to control hundreds of muscles independently. What this means, is that when you record from 96 electrodes simultaneously, many of the neurons picked up by the array are correlated, such that the resulting dimensionality is much lower than the number of neurons
3) An important step forward will be to develope optogenetic (or other) sensory write in, using pulses of light to activate neutrons in specific patterns that mimic priprioceptive signals from your limbs. This will increase the speed and robustness of movent via faster closed loop feedback.
4) Processing power. Currently it's typical to run decoders on real-time PC's. Creating an embedded processor capable of sufficiently low power operation with enough processing power to run the decode is non-trivial, especially if you want to implant this in the brain.
It is very unlikely, as suggested elsewhere, that current web tech will impact BMI research at all. The primary interesting tech is in the decode algorithm, which is a modified form of the Kalman filter. There is, however, a lot of room for hackers in research. I recently made the switch from working in defense, building robots and designing sensor fusion algorithms, to a phd in neuroscience. Probably won't pay as well long term, but it's far more rewarding and interesting! I'm surrounded by scientists that need better (software and hardware) tools and analysis methods. Also, an infusion of ideas and values aligned with open access publishing (or changing the scientific publishing model altogether), open source software, data and code sharing, etc. would generally benefit all and accelerate scientific research, but that's another topic worthy of more discussion elsewhere.