eeg signal background and real-time processing
TRANSCRIPT
EEG signal background and real-time processing
Robert Oostenveld
Donders Institute, Radboud University, Nijmegen, NL
Karolinska Institute, Stockholm, SE
Outline
Brain activity and how to measure it
The source of EEG signals
Controlling alpha oscillations
Realtime processing and closed-loop systems
Brain activity
spiking activity
(local) field potentials
magnetic fields
blood flow
blood oxigenation
biochemical concentrations
Methods to record brain activity
(sharp-tipped electrodes)
multi electrode array (c.f. Utah array)
sEEG multitrodes
ECoG surface electrodes
(voltage sensitive dyes)
scalp EEG
MEG
NIRS
arterial spin labeling
BOLD
MRS
EEG Instrumentation
Recording EEG
Outline
Brain activity and how to measure it
The source of EEG signals
Controlling alpha oscillations
Realtime processing and closed-loop systems
pre-synapticaction potential
post-synapticpotential
electric current
Superposition of source activity
Standard electrode placement
High-density electrode placement
Outline
Brain activity and how to measure it
The source of EEG signals
Controlling alpha oscillations – and others
Realtime processing and closed-loop systems
Adapted from Jensen & Mazaheri (2010) Frontiers Neurosci.
a
b
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Adapted from Jensen & Mazaheri (2010) Frontiers Neurosci.
a
b
c
Adapted from Jensen & Mazaheri (2010) Frontiers Neurosci.
a
b
c
High alpha = inattention
Low alpha = attending
Other brain signals used in EEG-BCI
pay attention to one feature, ignore others
SSVEP – steady state visual evoked potential
P300 – positivity around 300 ms after stimulus
imagine movements
Mu rhythm – mix of 10 and 20 Hz over sensory-motor regions
Outline
Brain activity and how to measure it
The source of EEG signals
Controlling alpha oscillations
Realtime processing and closed-loop systems
Conventional experiment
M/EEG, fMRI,...data source
analysis
stimuluspresentation hard disk
hard disk
collect many data from many subjects, analyse later
Realtime experiment / BCI loop
• Challenge: timely handling of incoming data, preprocessing, analysis, sending outputs
M/EEG, fMRI,...data source
preprocessingfeature extract.
analysis
stimuluspresentation
Buffering relaxes timing constraints...
• analysis side can pick data when convenient
• can look back in time if needed
M/EEG, fMRI,...data source
analysissoftware
stimuluspresentation
datastream or
ringbuffer
... and facilitates talking to different devices more easily
MEG: CTF,Neuromag
fMRI:Siemens
EEG: TMSI, Biosemi, OpenBCI
NIRS:Artinis
analysissoftware
FieldTripbuffer
ECoG:Neuralynx,Micromed
Multiple applications for analysis etc.
applications can communicate through buffer („events“)
FieldTripbuffer
analysissoftware
analysissoftware
otherplatforms
onlinedisplay
MEG: CTF,Neuromag
fMRI:Siemens
EEG: TMSI, Biosemi, OpenBCI
NIRS:Artinis
ECoG:Neuralynx,Micromed
Extends naturally to pipelines
EEG system
„raw“EEGdata
translate into control signals
filter & re-reference
„clean“EEG data
monitor data qualitye.g. drift
loose electrodes
Concepts of pipeline sequence
artifactdetection
spectral estimation
classificationor regression
rawdata
“control” signal
many numbers few numbers
amplifier analysis computer
storage
Controlled device
Experimental controlTherapeutic operator
Subject
data
feedback signal
EE
G
co
ntro
l sig
na
l
da
taOptimization
Behavior, analysis and control signals
In green the basic minimal BCI setup.
In pink the additional feedback signal for a neurofeedback system.
In orange the registration and storage of all data to reconstruct and analyze the neurofeedback system.
In yellow the optimization of the analysis and/or control.
In red the control of the experimentor or therapist.
co
ntr
ol fe
ed
back
Pyt
ho
nm
od
ule
s
Red
is
FieldTrip buffer
USBCV/gate
webserver
USB-MIDI interface
OpenBCIinterface
audience/subjectartist/performer
scientist/engineer