PhD position in Theoretical Neuroscience available
Brain Imaging & Brain Dynamics
EEG and MEG as non-invasive windows into the brain
It is commonly agreed in the scientific community that the brain's nerve
cells communicate with each other by means of electric signals, the so-called
action potentials. The simultaneous activity of hundreds of neurons is required
to cause one single neuron to respond and send out a signal itself. Thus network
operations seem to be the carrier of information processing in the brain. These
operations can be 'observed' from the outside by means of measuring the electric
and magnetic activity caused by the processing of electric nerve signals of the
networks. The electric potentials on the skull measured by electroencephalography (EEG)
and magnetic fields around the skull measured by magnetoencephalography (MEG)
are primarily generated by neocortical sources and display a rich
spatiotemporal dynamics on the scale of millimeter and milliseconds. They are the
ideal tool to study human brain dynamics non-invasively. The complexity of these
data requires application of sophisticated data analysis, as well as guidance by
theories and models.
Electroencephalography
EEG recorded with many electrodes leads to patterns of the electric potential on the scalp which are coherent in space i.e. there are only one or two maxima and minima over the entire array of electrodes. The dynamics of these patterns show complex behavior in time. The data shown here was recorded using 16 electrodes over the occipital region for the case of alpha-EEG and 25 electrodes for epileptic-EEG. In both cases the entire spatiotemporal dynamics can be reconstructed as a superposition of only a few spatial patterns and their corresponding amplitudes in time. The MPEG-movies show these relevant patterns (5 in the case of alpha-EEG and 3 for the epileptic-EEG) and the time series of the amplitudes together with the actual spatiotemporal pattern of neural electric activity.
The EEG-data
were provided by D. Lehmann, Universit�tshospital Z�rich.
For more details refer to:
- Fuchs A., Friedrich R., Haken H., Lehmann D.: `Spatio-Temporal Analysis of Multichannel alpha-EEG Map Series', in: Computational Systems -- Natural and Artificial, H. Haken, ed., Springer, Berlin (1987)
- Friedrich R., Fuchs A., Haken H.: `Spatio-Temporal EEG Patterns', in: Rhythms in Physiological Systems, H. Haken, H.P. Koepchen, eds., Springer, Berlin (1991)
Magnetoencephalography
The following MPEG-movies show the spatiotemporal patterns of neural magnetic activity recorded from a human subject in three different conditions:
- Listening to tones that were delivered with a delay of about 5s. A random time was added to prevent stimulus prediction. The signal is an average over about 80 stimulus presentations.
- Reacting to acoustic stimuli. The same stimulus presentation as in (1) but now the subject was told to press on an air cushion as soon as possible after the tone was heard.
- Synchronizing with a rhythm. Here the tones were presented regularly with a frequency of 1 Hz. The subject was told to press the air cushion in synchrony with the stimulus.
- Auditory Evoked Fields (MPEG 323K)
- Reacting to an Auditory Stimulus (MPEG 556K)
- Synchronizing to Rhythmic Tones (MPEG 668K)
The signals were interpolated in space to obtain a smooth pattern using a two-dimensional spline technique. The white vertical line indicates the point in time for the frame with respect to the stimulus (green line) and the response (yellow line). The time is given in milliseconds with respect to the onset of the stimulus.
The MEG-data were recorded using the CTF system at the Brain Behavior Laboratory, Simon Fraser University, Burnaby, Canada (Director H. Weinberg).
Analysis and reconstruction of magnetoencephalographic brain data
This MPEG-movie shows the spatiotemporal dynamics of neural magnetic activity recorded during a perceptual-motor coordination task. A subject is exposed to a rhythmic stimulus and instructed to press a button in the middle of two consecutive tones i.e. to syncopate with the stimulus. After every ten tones the time interval between the tones is decreased. At a certain frequency (around 1.75 Hz) the subject is no longer able to keep the syncopation pattern and switches spontaneously to a coordination pattern for which the stimulus and the response are synchronized. During this task the subject's MEG was recorded over the left temporal parietal region using a 37-channel BTI SQuID device. The signals from about 30 runs are averaged.
The analysis and modeling performed for this experiment are summarized in the movie. The image in the upper left shows the spatiotemporal data interpolated in space. The analysis shows that the spatiotemporal dynamics can be reconstructed by a superposition of 3 spatial non-orthogonal patterns and their corresponding amplitudes. The image in the upper middle shows the pattern reconstructed from these 3 modes. The upper red and yellow time series and the upper green time series represent the corresponding amplitudes. Vertical red lines mark the points in time where the frequency of the stimulus was changed; we refer to a region with a constant stimulus frequency as a plateau. On the first two plateaus the subject syncopates with the stimulus whereas on the last two plateaus the movement and the stimulus are synchronized (the plateaus where the transition takes place are not shown here). The dynamics of the 3 spatial modes above was modeled using coupled nonlinear oscillators. The time series from this model are the lower of the yellow and red and the lower of the green curves. Notice that they match quite well the experimental data but are less noisy. The image in the upper right corner is the reconstruction of the entire spatiotemporal dynamics from the model i.e. the superposition of the time series multiplied with the corresponding spatial patterns.
For more details refer to:
- Kelso J.A.S., Bressler S.L., Buchanan S., DeGuzman G.C., Ding M., Fuchs A., Holroyd T.: `Cooperative and critical phenomena in the human brain revealed by multiple SQUIDs', in: Measuring Chaos in the Human Brain, D. Duke & W. Pritchard, eds., World Scientific, Singapore (1991)
- Kelso J.A.S., Bressler S.L., Buchanan S., DeGuzman G.C., Ding M., Fuchs A., Holroyd T.: `Phase transition in human brain and behavior', Phys. Lett. A 169: 134-144 (1992)
- Fuchs A., Kelso J.A.S., Haken H.: `Phase Transitions in the Human Brain: Spatial Mode Dynamics', Int. J. Bifurc. Chaos, 2: 917-939 (1992)
- Jirsa V.K., Friedrich R., Haken H., Kelso J.A.S.: `A theoretical model of phase transitions in the human brain', Biol. Cybern. 71: 27-35 (1994)
- Jirsa V.K., Friedrich R., Haken H.: 'Reconstruction of the spatiotemporal dynamics of a human magnetoencephalogram', Physica D89, 100-122 (1995)
143 Channel MEG
The data were collected using the 143 SQuID system developed by CTF Systems Inc. in Vancouver, Canada. More information about the experiments are available for the 143 Channel MEG and the simultaneous MEG/EEG recordings. One of the experiments (the visual evoked fields) was done by members of the Brain Behavior Laboratory, Simon Fraser University, Burnaby, Canada, the other data was collected by CTF staff.