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What is the most advanced open source solution to the brain computer interface issue? Afaik they had gotten pretty good at decoding even the low sensor density

What is the most advanced open source solution to the brain computer interface issue? Afaik they had gotten pretty good at decoding even the low sensor density data into actionable input, but all solutions suffer from input/compute lag. So that said, FMRI's won't work for realtime will it due to how long scans take? So EEG's seem to be the only choice. Perhaps to make up for accuracy you have to increase sensor density enough and you should get a system thats fairly accurate. My guess is that most modern attempts have poor sensor density.

yorwba 9y ago
And part of the reason EEGs have poor sensor density is that attaching and removing them is a pain in the ass, especially if you have long hair. I participated in a study where my EEG was taken while I watched some random videos, and half the time was spent on putting enough conductive gel in my hair below the sensors to get a stable signal, and afterwards I had to shower to get rid of the stuff. There was a bald guy in the study who amazed everyone when he could just put on the cap to get a signal, so EEG might work as brain-computer interface for some people. But for the general population, it's just too much of a hassle.
- neuromantik8086 9y ago
  EEG nets that use saline solutions are much more manageable than gel-based nets from what I've seen (disclaimer: only ever had to use the saline solution nets). That said, avoiding crosstalk between electrodes / bridging was a bitch.
blubbi 9y ago
See here for all the tradeoffs involved in current brain imaging technology: https://waitbutwhy.com/2017/04/neuralink.html https://waitbutwhy.com/2017/04/neuralink.html Long story short, if you want a real time interface that also has high spatial resolution, you need to get invasive (and increase the number of electrodes by a lot)
EmlynC 9y ago
There are many open-source solutions for BCI projects like BCI2000 (http://www.schalklab.org/research/bci2000 http://www.schalklab.org/research/bci2000), OpenVibe (http://openvibe.inria.fr/ http://openvibe.inria.fr/) and EEGLab (https://sccn.ucsd.edu/eeglab/index.php https://sccn.ucsd.edu/eeglab/index.php). That's based on the kinds of tools that our customers use. Most of these, aren't as pretty as tool like Neurovis, but in reality most of the information that we make use of to control prosthetics or signal intention involve looking at the temporal-frequency relationships between and within broad regions of the brain. There isn't a lot that you gain from just looking at the brain light up like this for BCI — the main use for a visualisation like this, is as the docs say, for diagnosis and determination of epilepsy since in epilepsy the activity you'd see is much higher than usual. EEG has better temporal resolution than FMRI; you are measuring the electrical activity rather than vascular changes, the former changes more rapidly than the other. EEG, however, is just the surface activity of the brain, so you don't get information about 'deeper' (physically) brain processes; this is where FMRI is invaluable. EEG is also limited to the size of the electrodes and how many electrodes you can physically place in one location. 256 electrodes on an EEG cap is about the limit you can get to. Electrocorticography (ECog) involves implanting electrodes on the dura, this can substantially improve the density of electrodes in a given area, however this doesn't measure deep brain activity and we have no way of leaving the electrode grid in place for long periods of time without risking infection. For BCI, we've been able to classify more classes of data using ECog than EEG — research by Kyousuke Kamada and Gerwin Schalk are informative. It's a very promising area if we can work out how to implant the electrodes, seal the skull and telemeter data out. Magnetoencephalography (MEG) can help with measuring deep brain activity, but there are other tradeoffs to consider. Essentially, the point where we are now is combining multiple techniques to get the best temporal, spatial and frequential compromises. Thus in answer to your question; no FMRI is not great for realtime responses, measuring the electrical activity has better temporal properties so EEG and ECog work better here. Sensor density is part of the problem, but once you solve density you then need to consider how you'll deal with deep brain measurements. Background; I own a company that distributes BCI equipment for g.tec medical engineering in the UK. We've been operating in this space for 8 years. I have a PhD in Pharmacology and a speciality in electrophysiology.
- 9y ago
SubiculumCode 9y ago
There are real time fMRI applications. You just won't get to have one in your home. 3 Tesla's dude. That makes metal fly, and is hyper expensive.

yorwba 9y ago

And part of the reason EEGs have poor sensor density is that attaching and removing them is a pain in the ass, especially if you have long hair. I participated in a study where my EEG was taken while I watched some random videos, and half the time was spent on putting enough conductive gel in my hair below the sensors to get a stable signal, and afterwards I had to shower to get rid of the stuff. There was a bald guy in the study who amazed everyone when he could just put on the cap to get a signal, so EEG might work as brain-computer interface for some people. But for the general population, it's just too much of a hassle.

neuromantik8086 9y ago
EEG nets that use saline solutions are much more manageable than gel-based nets from what I've seen (disclaimer: only ever had to use the saline solution nets). That said, avoiding crosstalk between electrodes / bridging was a bitch.

blubbi 9y ago

See here for all the tradeoffs involved in current brain imaging technology: https://waitbutwhy.com/2017/04/neuralink.html https://waitbutwhy.com/2017/04/neuralink.html Long story short, if you want a real time interface that also has high spatial resolution, you need to get invasive (and increase the number of electrodes by a lot)

EmlynC 9y ago

There are many open-source solutions for BCI projects like BCI2000 (http://www.schalklab.org/research/bci2000 http://www.schalklab.org/research/bci2000), OpenVibe (http://openvibe.inria.fr/ http://openvibe.inria.fr/) and EEGLab (https://sccn.ucsd.edu/eeglab/index.php https://sccn.ucsd.edu/eeglab/index.php). That's based on the kinds of tools that our customers use. Most of these, aren't as pretty as tool like Neurovis, but in reality most of the information that we make use of to control prosthetics or signal intention involve looking at the temporal-frequency relationships between and within broad regions of the brain. There isn't a lot that you gain from just looking at the brain light up like this for BCI — the main use for a visualisation like this, is as the docs say, for diagnosis and determination of epilepsy since in epilepsy the activity you'd see is much higher than usual. EEG has better temporal resolution than FMRI; you are measuring the electrical activity rather than vascular changes, the former changes more rapidly than the other. EEG, however, is just the surface activity of the brain, so you don't get information about 'deeper' (physically) brain processes; this is where FMRI is invaluable. EEG is also limited to the size of the electrodes and how many electrodes you can physically place in one location. 256 electrodes on an EEG cap is about the limit you can get to. Electrocorticography (ECog) involves implanting electrodes on the dura, this can substantially improve the density of electrodes in a given area, however this doesn't measure deep brain activity and we have no way of leaving the electrode grid in place for long periods of time without risking infection. For BCI, we've been able to classify more classes of data using ECog than EEG — research by Kyousuke Kamada and Gerwin Schalk are informative. It's a very promising area if we can work out how to implant the electrodes, seal the skull and telemeter data out. Magnetoencephalography (MEG) can help with measuring deep brain activity, but there are other tradeoffs to consider. Essentially, the point where we are now is combining multiple techniques to get the best temporal, spatial and frequential compromises. Thus in answer to your question; no FMRI is not great for realtime responses, measuring the electrical activity has better temporal properties so EEG and ECog work better here. Sensor density is part of the problem, but once you solve density you then need to consider how you'll deal with deep brain measurements. Background; I own a company that distributes BCI equipment for g.tec medical engineering in the UK. We've been operating in this space for 8 years. I have a PhD in Pharmacology and a speciality in electrophysiology.

9y ago

SubiculumCode 9y ago

There are real time fMRI applications. You just won't get to have one in your home. 3 Tesla's dude. That makes metal fly, and is hyper expensive.