6 ms·

The consumer grade EEG's you would use for this, like Open BCI, place rudimentary sensors on the scalp. There just isn't enough information from these types of

The consumer grade EEG's you would use for this, like Open BCI, place rudimentary sensors on the scalp. There just isn't enough information from these types of sensors to give you a real look at what signals are occurring in the brain. This is a fundamentally flawed premise and is nothing more than a toy. Real brain research must be done with FMRIs or much more accurate EEG's than consumers have access to, and institutions with such advanced tech already have vis software.

xab9 9y ago
I had multiple MR and CT scans, some EEG - from all these only EEG is kinda "realtimish", isn't it? Do we have any technology in these days that can _map_ surface electrical changes to brain internals (depth data) or anything that can work in true 3d?
- frereubu 9y ago
  Yep, only EEG gives you that kind of information. fMRI takes a lot of post-processing with complex statistics to produce any kind of useful information. I worked on a study that used fMRI to study the involvement of early visual areas in the cortex during reading tasks, and when processing long runs we'd get on with other stuff while the data was being processed. There isn't any existing tech to take surface data and "map" it to internal states because there isn't a simple relationship between on and the other. For real-time recording of activity deeper in the brain than a few centimetres you need to implant electrodes during surgery, which is obviously only something that happens in humans when that person needs brain surgery already. There's some interesting stuff being done around decision-making with implanted electrodes in monkeys, but that's understandably not to everyone's taste.
  - omginternets 9y ago
    > fMRI takes a lot of post-processing with complex statistics to produce any kind of useful information. So does EEG. The reason EEG is closer to real-time than fMRI is because of the sampling rate. With fMRI, .9 Hz is considered quite good. For EEG, 2000 Hz is considered standard.
    - frereubu 9y ago
      Thanks for the clarification. I've only worked with fMRI, so wasn't aware of the ins and outs of EEG processing despite being aware of the spacial / temporal resolution difference. It makes this method even more suspicious!
    - nabla9 9y ago
      Standard? 2000 Hz sampling rate may be used with intracranial electrodes. If the EEG is measured from the scalp 200-250 Hz sampling rate is usually good enough. It enables EEG recordings up to 80-90 Hz. Most clinical uses are interested EEG below 40 Hz.
      - omginternets 9y ago
        My mistake: I got mixed up and reported standard sampling rates for MEG. You are, of course, correct.
  - SubiculumCode 9y ago
    There are real questions regarding the degree of locality information from eeg. The temporal resolution though is measured in ms. There are real time fMRI research...particularly in the use of classifiers. The temporal resolution tends to be around 2-7 seconds (2 seconds for each acquisition, but the hemodynamic response is over the course of 7+ seconds..
  - neuromantik8086 9y ago
    > when processing long runs we'd get on with other stuff while the data was being processed. The main reason why fMRI processing takes so long is the reluctance of the major neuroimaging suites to embrace GPUs. A newer suite, BROCCOLI [1], is substantially faster but has much less adoption and isn't quite as full-featured as the other suites. [1] https://www.frontiersin.org/articles/10.3389/fninf.2014.00024/full https://www.frontiersin.org/articles/10.3389/fninf.2014.0002...
    - Batman10232 9y ago
      Not just GPUs, most labs don't embrace parallelism in general. I managed to get a 55x speedup between serial and parallel versions using the same program (SPM) by using several mid-grade computers and caching (Sorry I don't have anything written on this, I've been putting it off). It's hard to get researchers to switch using the algorithms that they know and are comfortable with, which is why I think stuff like BROCCOLI, or PSOM haven't taken off.
      - deleted 9y ago
        [deleted]
  - Batman10232 9y ago
    EEG can do real time imaging because the sampling rate is much better. EEG also requires fairly intensive data processing, but usually it can be done faster than fMRI because: 1. There is often less/different information in EEG. If you have 64 nodes, you will have less information to process than the >100000 voxels in fMRI. 2. There have been more reasons to look at EEG in real time. fMRI analyses are generally done with group level statistics, so usually you have to run many participants which takes weeks-months anyways. >There isn't any existing tech to take surface data and "map" it to internal states Eh, sort of. Algorithms like LORETA which do source reconstruction have been around for a while, and do an OK job of finding the general area of the source of a signal.
- yoz-y 9y ago
  You can do LORETA inverse solution to go from EEG to voxels which approximate internal sources. The problem is that this model does several suppositions about the brain structure that may or may not be true. In my opinion, surface currents are only good for surface sources, as the neurons in cortex are aligned and thus generate relatively strong currents in comparison to neurons inside the brain which are positioned "randomly".
- lostlogin 9y ago
  You can do real-time fMRI for relatively simple tasks. Saying a word, tapping a finger, moving the tongue. “Real-time” is the wrong phrasing as the data builds up over several runs but you see it as it builds and get something useful a minute of two into acquisition.
arca_vorago 9y ago
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.
stinos 9y ago
FMRIs or much more accurate EEG's Or neural recordings with electrodes. Better spatial resolution than EEG and fMRI and way better time resolution than fMRI.
- frereubu 9y ago
  If you mean surface electrodes, then that is EEG: ElectroEncephaloGram. If you mean electrodes inside the brain, then you're talking brain surgery. I'm not sure what point you're making here - could you elucidate?
  - stinos 9y ago
    I did mean electrodes in the brain (or spine) and mentioned that for completeness, to make it clear there's another method besides fMRI and EEG. Which indeed has the obvious disadvantage it involves some surgery, but does the type of signal recorded with it does have advantges over the other methods.
    - SubiculumCode 9y ago
      When available in humans, that data is amazing. It is used frequently in animal models though.
GistNoesis 9y ago
I'm no expert, but what about seeing the brain using radio-waves diffraction pattern. You take an emitting antenna in-front of the person, 1 meter behind him you make a grid array of Software Defined Radios (like 10x10=100 SDR (SDR are so cheap that it will be ~ the price of an OpenBCI set) ), and you record the diffraction/interference pattern, then you software analyze it to produce a 3d image via solving the inverse scattering problem, to get the fluids flows and densities (you should even get the speeds through Doppler)). My simple back of the envelope calculations, says that at 5Ghz we should rather easily get a spatial resolution of lambda/4=1.5 cm, maybe more using super resolution techniques. Going to 60Ghz, we should soon be able to reach millimeters spatial resolution. It obviously won't reach the quality levels of FMRIs. Can someone from the field tell what kind of bandwidth we should expect from such a setup?
- yoz-y 9y ago
  EEG noise to signal ratio is so ridiculously low that you really need to be as close to the brain as possible. Any muscular activity produces electrical currents an order of magnitude higher. As a side note: what an FMRI sees and what an EEG measures is fundamentally different. EEG can reliably only detect the Pyramidal neurons in the cortex an MRI can see below that.
  - GistNoesis 9y ago
    I'm not suggesting that we measure the signal emitted by the brain like EEG do. I'm suggesting that we look at the fluids movements like FMRI do but using diffraction like xray-imaging with bigger wavelengths.
    - omginternets 9y ago
      >I'm suggesting that we look at the fluids movements like FMRI do but using diffraction like xray-imaging with bigger wavelengths. What would we gain from using RF-diffraction as opposed to MR? The major advantage of fMRI is that you're measuring a so-called Blood-Oxygen-Level-Dependent (BOLD) signal. That is, you're looking at a contrast between oxygenated and de-oxygenated blood, which is more interesting than just looking at where blood (of all types) is going. The underlying assumption is that brain volumes consume oxygen at a rate roughly proportional to the level neuronal activity. As such, a BOLD signal is really what you want.

xab9 9y ago

I had multiple MR and CT scans, some EEG - from all these only EEG is kinda "realtimish", isn't it? Do we have any technology in these days that can _map_ surface electrical changes to brain internals (depth data) or anything that can work in true 3d?

frereubu 9y ago
Yep, only EEG gives you that kind of information. fMRI takes a lot of post-processing with complex statistics to produce any kind of useful information. I worked on a study that used fMRI to study the involvement of early visual areas in the cortex during reading tasks, and when processing long runs we'd get on with other stuff while the data was being processed. There isn't any existing tech to take surface data and "map" it to internal states because there isn't a simple relationship between on and the other. For real-time recording of activity deeper in the brain than a few centimetres you need to implant electrodes during surgery, which is obviously only something that happens in humans when that person needs brain surgery already. There's some interesting stuff being done around decision-making with implanted electrodes in monkeys, but that's understandably not to everyone's taste.
- omginternets 9y ago
  > fMRI takes a lot of post-processing with complex statistics to produce any kind of useful information. So does EEG. The reason EEG is closer to real-time than fMRI is because of the sampling rate. With fMRI, .9 Hz is considered quite good. For EEG, 2000 Hz is considered standard.
  - frereubu 9y ago
    Thanks for the clarification. I've only worked with fMRI, so wasn't aware of the ins and outs of EEG processing despite being aware of the spacial / temporal resolution difference. It makes this method even more suspicious!
  - nabla9 9y ago
    Standard? 2000 Hz sampling rate may be used with intracranial electrodes. If the EEG is measured from the scalp 200-250 Hz sampling rate is usually good enough. It enables EEG recordings up to 80-90 Hz. Most clinical uses are interested EEG below 40 Hz.
    - omginternets 9y ago
      My mistake: I got mixed up and reported standard sampling rates for MEG. You are, of course, correct.
- SubiculumCode 9y ago
  There are real questions regarding the degree of locality information from eeg. The temporal resolution though is measured in ms. There are real time fMRI research...particularly in the use of classifiers. The temporal resolution tends to be around 2-7 seconds (2 seconds for each acquisition, but the hemodynamic response is over the course of 7+ seconds..
- neuromantik8086 9y ago
  > when processing long runs we'd get on with other stuff while the data was being processed. The main reason why fMRI processing takes so long is the reluctance of the major neuroimaging suites to embrace GPUs. A newer suite, BROCCOLI [1], is substantially faster but has much less adoption and isn't quite as full-featured as the other suites. [1] https://www.frontiersin.org/articles/10.3389/fninf.2014.00024/full https://www.frontiersin.org/articles/10.3389/fninf.2014.0002...
  - Batman10232 9y ago
    Not just GPUs, most labs don't embrace parallelism in general. I managed to get a 55x speedup between serial and parallel versions using the same program (SPM) by using several mid-grade computers and caching (Sorry I don't have anything written on this, I've been putting it off). It's hard to get researchers to switch using the algorithms that they know and are comfortable with, which is why I think stuff like BROCCOLI, or PSOM haven't taken off.
    - deleted 9y ago
      [deleted]
- Batman10232 9y ago
  EEG can do real time imaging because the sampling rate is much better. EEG also requires fairly intensive data processing, but usually it can be done faster than fMRI because: 1. There is often less/different information in EEG. If you have 64 nodes, you will have less information to process than the >100000 voxels in fMRI. 2. There have been more reasons to look at EEG in real time. fMRI analyses are generally done with group level statistics, so usually you have to run many participants which takes weeks-months anyways. >There isn't any existing tech to take surface data and "map" it to internal states Eh, sort of. Algorithms like LORETA which do source reconstruction have been around for a while, and do an OK job of finding the general area of the source of a signal.
yoz-y 9y ago
You can do LORETA inverse solution to go from EEG to voxels which approximate internal sources. The problem is that this model does several suppositions about the brain structure that may or may not be true. In my opinion, surface currents are only good for surface sources, as the neurons in cortex are aligned and thus generate relatively strong currents in comparison to neurons inside the brain which are positioned "randomly".
lostlogin 9y ago
You can do real-time fMRI for relatively simple tasks. Saying a word, tapping a finger, moving the tongue. “Real-time” is the wrong phrasing as the data builds up over several runs but you see it as it builds and get something useful a minute of two into acquisition.

arca_vorago 9y ago

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.

stinos 9y ago

FMRIs or much more accurate EEG's Or neural recordings with electrodes. Better spatial resolution than EEG and fMRI and way better time resolution than fMRI.

frereubu 9y ago
If you mean surface electrodes, then that is EEG: ElectroEncephaloGram. If you mean electrodes inside the brain, then you're talking brain surgery. I'm not sure what point you're making here - could you elucidate?
- stinos 9y ago
  I did mean electrodes in the brain (or spine) and mentioned that for completeness, to make it clear there's another method besides fMRI and EEG. Which indeed has the obvious disadvantage it involves some surgery, but does the type of signal recorded with it does have advantges over the other methods.
  - SubiculumCode 9y ago
    When available in humans, that data is amazing. It is used frequently in animal models though.

GistNoesis 9y ago

I'm no expert, but what about seeing the brain using radio-waves diffraction pattern. You take an emitting antenna in-front of the person, 1 meter behind him you make a grid array of Software Defined Radios (like 10x10=100 SDR (SDR are so cheap that it will be ~ the price of an OpenBCI set) ), and you record the diffraction/interference pattern, then you software analyze it to produce a 3d image via solving the inverse scattering problem, to get the fluids flows and densities (you should even get the speeds through Doppler)). My simple back of the envelope calculations, says that at 5Ghz we should rather easily get a spatial resolution of lambda/4=1.5 cm, maybe more using super resolution techniques. Going to 60Ghz, we should soon be able to reach millimeters spatial resolution. It obviously won't reach the quality levels of FMRIs. Can someone from the field tell what kind of bandwidth we should expect from such a setup?

yoz-y 9y ago
EEG noise to signal ratio is so ridiculously low that you really need to be as close to the brain as possible. Any muscular activity produces electrical currents an order of magnitude higher. As a side note: what an FMRI sees and what an EEG measures is fundamentally different. EEG can reliably only detect the Pyramidal neurons in the cortex an MRI can see below that.
- GistNoesis 9y ago
  I'm not suggesting that we measure the signal emitted by the brain like EEG do. I'm suggesting that we look at the fluids movements like FMRI do but using diffraction like xray-imaging with bigger wavelengths.
  - omginternets 9y ago
    >I'm suggesting that we look at the fluids movements like FMRI do but using diffraction like xray-imaging with bigger wavelengths. What would we gain from using RF-diffraction as opposed to MR? The major advantage of fMRI is that you're measuring a so-called Blood-Oxygen-Level-Dependent (BOLD) signal. That is, you're looking at a contrast between oxygenated and de-oxygenated blood, which is more interesting than just looking at where blood (of all types) is going. The underlying assumption is that brain volumes consume oxygen at a rate roughly proportional to the level neuronal activity. As such, a BOLD signal is really what you want.