2 Electroencephalography (EEG) Basic principles & Applications Flashcards
- Why Electroencephalography (EEG)?
Excellent time resolution
- Cognitive, perceptual, linguistic, emotional and motor processes are fast and dynamic
- For example, consider theta band (4-8 Hz), a ‘slow’ rhythm but quite ‘fast’ for our conscious experience
- Or consider gamma (30-80 Hz)
2.
List 4 positive aspects of EEG.
- Direct indicator of neuronal activity
- Multidimensional (time, space, frequency, power, phase, connectivity etc)
- Portability (observing brain in action)
- Relatively inexpensive (20k - vs 2million fMRI)
3.
Name some negative qualaties of EEG
- It is not well-suited for precise functional localization
- It is not well-suited for measuring deep brain structures (e.g., putamen, thalamus, nucleus accumbens)
- Sub-optimal method: where in the brain does process X occur or is information Y stored
- It is also not very well-suited to study very slowly fluctuating process with uncertain and variable time course (fMRI is better)
4.
EEG reflects the differences of ………………………… over
time, created by the ……….. flows originating from
……………………….
EEG reflects the differences of electrical potential over
time, created by the current flows originating from
neuronal populations.
5.
Name the two types of neuronal electrical activity.
(i) Action potential (AP) (an action potential is a short-lasting event in which the electrical membrane potential of a cell rapidly rises and falls, following a consistent trajectory)
(ii) Postsynaptic potentials (PSPs) are changes in the membrane potential of the postsynaptic terminal of a chemical synapse. PSPs are graded potentials, and should not be confused with action potentials although their function is to initiate or inhibit action potentials
EEG reads signals from PSPs in groups of millions of neurons.
6.
What are sodium channels (Na+)?
Sodium channels are integral membrane proteins that form ion channels, conducting sodium ions (Na+) through a cell’s plasma membrane
7.
Mediation of the Action Potential by Voltage-Gated Sodium Channels:
List the 6 stages
- Resting State – Both sodium and potassium channels are closed and membrane is in the resting state.
- Threshold - A stimulus opens some sodium Na+ channels. If the influx of sodium Na+ achieves threshold, then more channels are opened, triggering an action potential.
- Depolarization Phase- Activation gates of sodium channels are open, but the potassium K+ channels remain closed. Sodium ions rush into the cell, the interior of the cell becomes more positive
- Repolarization phase- Inactivation gates close channels, and potassium channels open. Potassium ions leave the cell, and the loss of positive charge causes the inside of the cell to become more negative.
- Undershoot - Both gates of the sodium channels are closed, but potassium channels remain open because their relatively slow gates have not had time to respond to repolarization of the membrane. Within another millisecond or two, the resting state is restored and the system is ready to respond again.
- Back to Resting State ready to fire again
8.
Propogation of action potential - how are electrodes placed?
Electrodes may be placed along an axon and will collect data at different times depending on the direction of the action potential.
9.
…………………. cause local changes in postsynaptic membrane potentials, through ……………………….. Information transmits with some delay on the order of a millisecond.
Besides ……………….. there are ……………………. or gap junctions. Ions flow directly through large channels into adjacent cells, with no time delay.
Chemical synapses cause local changes in postsynaptic membrane potentials, through neurotransmitters. Information transmits with some delay on the order of a millisecond.
Besides chemical synapses there are electrical synapses, or gap junctions. Ions flow directly through large channels into adjacent cells, with no time delay.
10.
Generation of Post-Synaptic Potential (PSP)
Generation of PSP:
- When the AP reaches the presynaptic axon end, a neurotransmitter is released into the synaptic cleft
- The neurotransmitter binds to the receptor of the postsynaptic neuron by opening or closing ion channels
- This leads to a graded change in membrane potential
11.
What are the two types of post-synaptic potential (PSP)?
- Excitatory PSP (for excitatory synapse - positive potential)
- Inhibitory PSP (for inhibitor synapse - negative potential)
A PSP is an electrical potential initiated at a postsynpatic site that can vary in amplitude and spreads passively across the cell membrane, decreasing in strength with time and distance
12.
Recording Postsynaptic Potentials:
Draw an image of both excitatory and inhibitory neurons being read by EEG electrodes.
Red is excitatory (+)
Blue is inhibitory (-)
Depending on the neurotransmitter that is released the post synaptic potential can be either negative or positive.
- Electrical Signals are the Vocabulary of the Nervous System
…………. perform information processing to integrate ………………………..
A …………………. will fire an ……………………….. if a …………………. that exceeds threshold reaches its …………………….
Generally the combined effect of many …………………………….. is required for a …………………… neuron to fire.
Neurons perform information processing to integrate synaptic inputs.
A postsynaptic neuron will fire an action potential if a depolarization that exceeds threshold reaches its axon hillock.
Generally the combined effect of many excitatory synapses is required for a post-synaptic neuron to fire.
14.
Spatial Summation in a Postsynaptic Cell (Part 1)
…………………………… cause a cell to fire.
Excitatory inputs cause a cell to fire.
15.
Spatial Summation in a Postsynaptic Cell (Part 2)
……………….. also plays a role.
Inhibition also plays a role.
Inhibition counteracts excitation, no AP
16.
There are two types of summations:
What is spatial summation?
Spatial summation is the summing of potentials that come from different parts of the cell. If the overall sum – of EPSPs and IPSPs – can depolarize the cell at the axon hillock, an action potential will occur.
17.
There are two types of summations:
What is temporal summation?
Temporal summation is the summing of potentials that arrive at the axon hillock at different times.
The closer together in time that they arrive, the greater the summation and possibility of an action potential.
18.
…………….. are primarily produced by summation of ……………………… of millions of …………….
EEG signals are primarily produced by summation of postsynaptic potentials of millions of neurons
19.
List 5 things EEG is not:
Include statements on:
meaurement, sensitivity, brain regions and speed.
- It cannot measure all neural events
- It cannot measure individual molecular or synaptic events nor it can isolate events that are produced by a specific neurotransmitter or neuromodulator
- It is less sensitive to deep brain structures Field strength decreases exponentially with distance
- Neuronal populations in deeper structures are not arranged in a geometrically parallel fashion
- It is not very suitable to measure to very slow (< 0.1 Hz) or very high (> 100 Hz) fluctuations
20.
Sample MC Question EEG
Signals represent summation of:
A.action potentials
B.post-synaptic potentials
C.a mixture of A and B
D.neither A nor B
B. post-synaptic potentials
21.
Sample Brief Question
(a) Describe briefly how post-synaptic potentials are generated.
(b) Also describe briefly the procedure by which the post-synaptic potentials are integrated
a) When the AP reaches the presynaptic axon end, a neurotransmitter is released into the synaptic cleft
The neurotransmitter binds to the receptor of the postsynaptic neuron by opening or closing ion channels
This leads to a graded change in membrane potential
b) Neurons perform information processing to integrate synaptic inputs. Generally the combined effect of many excitatory synapses is required for a post-synaptic neuron to fire. IPSPs and EPSPs are summed together.
22.
Who undertook the first EEG recording in Humans?
Hans Berger (1873-1941)
23.
Draw a diagram of the EEG setup:
24.
Detail the electrondes used in EEG:
• Metal (conductive) –Ag/AgCl Electrodes (Silver electrodes with a thin coating of silver-chloride
- –Tin Electrodes
- –Goldcap Electrodes
•The conductivity should be good between the electrode and the scalp –Electrode gel to reduce the impedance/resistance
- –Impedance below 5 Kilo Ohms
- –Scalp preparation (removal of dead skin cells with alchohol cleaner wipes)
•Active Electrodes (relatively new last decade or so)
- –Integrated pre-amplifier
- –Faster preparation time
25.
What locations are used for EEG electrode placement?
- International 10-20 Electrode Placement System Jasper (1958) EEG Clin Neurophysiol
- All electrondes are placed at certain locations related to specific distances - F for frontal - P parietel - T for Temporal
- Odd numbers are for left hemishphere
- Even numbers are for right hemisphere
26.
Electrode placement
Fp = ?
C = ?
O = ?
T = ?
P = ?
Fp = Frontal pole
C = Central
O = Occipital
T = Temporal
P = Parietal
27.
How many electrodes are used in:
a traditional
b Standard
c High density
a) Traditional 19
b) Standard 32-64
c) High density 128-256 (or more)
Pros: Better spatial sampling, Source reconstructions
Cons: Long preparation time, Electrolyte bridge, Poorer signal quality
Rule of Thumb: Unless you expect precisely localized brain activity, 64 electrodes will be sufficient
28.
What is the Three Steps Procedure with Active Electrodes?
- Select cap to suit the size of participant
- Apply gel to each electrode location in cap
- Connect electrodes
No hair is hard - the skin is exposed and the skin gets thickened and not very conductive.
If using passive electrodes, prepare the skin at first and then follow these 3 steps.
29.
The amplification is done by ……………………… The signal is amplified from a few ……… to a few ………..
List the 3 different types of electrodes.
The amplification is done by Differential Amplifiers. The signal is amplified from a few μVolts to a few Volts.
Three electrodes:
- Active Electrode (A) placed at the desired site
- Reference Electrode (R) placed elsewhere on the scalp
- Ground Electrode (G) placed elsewhere on the scalp/body
–Amplifies AG – RG (whereas AG = A – G; RG = R – G)
30.
Ambient noise reduction in EEG?
Elimination of ambient noise
- Works best when impedances are same (low) for A and R
- Amplifier gain: 5-10 K
- Optimal gain depends on the input potential and output range
31.
What is the reference site and what are three paractical criteria to use?
- Preferably a ‘neutral’ site (tip of the nose, the earlobes, the mastoids, the chin etc)
Three practical criteria:
- Choose a site that is convenient and comfortable
- Choose a site that does not induce hemispheric bias
- Choose a site used by other researchers in your field
32.
Most used ‘neutral’ references:
- average of two earlobes
- average of two mastoids
33.
Other referencing scheme:
Other referencing scheme:
- Average of all electrodes
- Current source density maps
- Reference free method
- Requires high density recording
- Less accurate for boundary electrodes
- Insensitive to deep sources
34
Why are analog filters required?
- Avoiding ‘aliasing’ (sampling frequency is less than 2 x maximum frequency)
- Reducing artefacts
35.
What are the 4 types of analog filters?
- Low pass
- High pass
- Band pass
- Band stop, Notch
Typically:
- High pass: 0.5 Hz (or 0.1 Hz for slow brain responses)
- Low pass 100 Hz
- Notch 50 Hz (for removing power line noise; 60 Hz in USA)
36.
Digitization (Analogue to Digital Conversion) is required for EEG what is the resolution and sampling frequency?
16/24 bit Resolution (216 or 16192 different voltage values can be coded by the ADC)
Sampling frequency (fs) should satisfy Nyquist Criterion
- fs > 2 fmax (fmax = max. frequency of interest) In practice, fs > 5fmax
Need to avoid aliasing (slow sample)
Niquist therorem - sampling rate must be at least twice the Hz of sampling frequency.
37.
Sample Questions:
Which filter is often used to remove line noise?
A.High pass filter
B.Band pass filter
C.Band stop filter (notch)
D.Low pass filter
C.Band stop filter (remember stop = notch filter!)
38.
For an EEG signal with maximum frequency of 70 Hz, aliasing occurs when
A. fs=256 Hz
B. fs=1024 Hz
C. fs=512 Hz
D. fs=128 Hz
D. fs=128 Hz
39.
What are probelms in EEG signals called?
Artefacts
40.
Describe Artifact Rejection:
Artifact Rejection
- Essentially a ‘signal detection problem’
- ‘Brute force approach’: Reject if over threshold (75-100 μV) artifacts usually have much larger amplitude
- Blink (Check vEOG, Topography, Polarity)
- Eye movement (Check hEOG, Step-like wave)
- Electrode shift (Shifting of potentials)
- Muscles (High frequency)
- Heart (Mostly in mastoid electrodes, Low frequency)
Problems
- Loss of significant portion of data
- Some participants are very prone to certain artifacts
- Some tasks essentially call for artifacts
41.
Is artifact correction a good idea?
An alternative to artefact rejection is artefact correction, where arithmetic algorithms are used to correct the data for the artefacts. But apply judiciously!
Philosophy: “Don’t throw the baby out with the dirty water, but clean the water and throw the dirt only!”
Simple method:
- Subtraction method (variance based)
- Filtering
42.
What is Independant Componant Analysis (ICA)
ICA is a quite powerful technique and is able (in principle) to separate independent sources linearly mixed in several sensors. For instance, when recording electroencephalograms (EEG) on the scalp, ICA can separate out artifacts embeded in the data (since they are usually independent of each other).
43.
How can artifacts be minimised over the whole EEG process? List 6 points.
- Electrical screening of the testing space (Faraday cage)
- Careful instruction of partipants to minimize movement; blink pauses
- Ensuring the participants in relaxed condition (to reduce muscle activity)
- Careful electrode application to minimize impedance
- Maintaining cool temperature and low himidity level inside lab (to reduce slow drift)
- Filtering (e.g., high-pass filter to remove slow-shifts [i.e., low-frequency fluctuations in the EEG], as well as low-pass filter to avoid aliasing=bandpass filter)
44.
What are the standard frequency bands?
- Delta: 0 – 4 Hz
- Theta: 4 – 7 Hz (Stage1- 3-7cps)
- Alpha: 8 - 14 Hz (Drowsy - 8 - 12 cps stage 2 12- 14 cps +K complexes)
- Beta: 15 - 30 Hz (Awake low voltage - random fast)
- Gamma > 30 Hz
Note: This division is arbitrary, mostly by convention
45.
Fourier Analysis
Transformation of the EEG into sine functions of various frequencies
46.
Name 2 Applications of the Spontaneous EEG.
- Cognitive Research
- Experiments with long-duration stimuli (i.e. task requiring sustained attention, ecologically appropriate stimuli)
- Monitoring sleep stages
- Clinical Research
- Epilepsy
- Detection of seizures
- Localization of focus/foci
- Prediction of seizure onset
- Monitoring the level of anaesthesia
- Detection of brain death
- Measurement of drug effects
- Detection of cerebral pathology, e.g., through blood supply problems
- Sleep disorders
- Almost all neurological disorders have EEG correlates
47.
Define Event Related /Evoked Potential (ERP/ EP)
- General class of potentials displaying stable time relationship to a definable reference event
- Reference event
- Onset/offset of a stimulus
- Motor response
- Decision moment
Terminology EP: Perception and clinical research
ERP: Experimental cognitive research
48.
……. are waveforms characterized by a series of …….. or …….. deflections at different latencies (known as …………)
ERPs are waveforms characterized by a series of positive (P) or negative (N) deflections at different latencies (known as ERP componants).
49.
What are the two ERP component types?
- Exogenous Components: Modulated by external characteristics of stimuli
- Endogenous Components: Modulated by internal characteristics
(But this distinction is not definite)
50.
ERP Model: Signal Averaging
What is the ERP hypothesis?
ERP Hypothesis: ERP is a signal (s) that appears superimposed and without interaction on the background or ongoing EEG which is considered random noise (n).
Below: (where i being the trial index x-th point of time N is the total trial number)
51.
ERP Model: Signal Averaging
What assumptions are made?
Assumptions:
- ERP is uncorrelated with background EEG
- Background EEG is random
- ERP is invariant across trials (same ERP is repeated over trials)
- Background EEG varies (randomly) from trial to trial
After averaging across trials, noise will cancel out and only the event related EEG response will remain.
52.
What are 5 advantages of ERP?
- ERPs are simple, fast to compute
- ERPs require very few analysis or parameters
- ERP has high temporal precision and accuracy
- ERP literature is quite mature
- ERP provides a good quality check
53.
What are ERP components?
An ERP component is a part of waveform with a circumscribed scalp distribution (physiological substrate) and a circumscribed relationship to experimental variables (functional substrate).
Examples:
MMN (mismatched negativity, 160-220 ms at central sites) N170 (face-related potential at occipital sites)
54.
Why study ERP components?
List 3 reasons.
Why study ERP components?
- Common language linking diverse experiments, paradigms etc
- Base for integrating ERP with other measures of brain activity
- Structure-function information
55.
What is the “baseline” period used for in ERP analysis?
“Baseline” period: In averaging, all trials are set (arithmetically) to have the same zero voltage at stimulus onset, so that only deviations from the baseline voltage are seen in the ERP, after stimulus presentation.
Baseline subtraction (mean of baseline period is subtracted)
56.
Averaging to form a …………….
Averaging to form a VEP (visually evoked potential).
57.
How many trials should be undertaken in EEG?
The number of trial depends on
- signal-to-noise characteristics
- the effect size
- the type of analysis to be performed
58.
…………………. increases as a function of the square root of the ……………………….
SNR (signal-to-noise-ratio) increases as a function of the square root of the number of trials.
Amount of noise left after averaging = (1/sqrtN)R
R = amount of noise on a single trial
N = total number of trial
59.
P300 (P3)?
The P300 (P3) wave is an event related potential (ERP) component elicited in the process of decision making.
60.
As an example a trial is looking at the P3 component with an amplitude is 20 μV. Noise in a single trial EEG is 50 μV.
List the S/N ratio for singel trial - two trials - 20 trials and 200 trials.
- The S/N ratio on a single trial = 20/50 = 0.4
- The S/N ratio of two trials = (√2) x 0.4 = 0.56
- The S/N ratio of 20 trials = (√20) x 0.4 = 1.79
- The S/N ratio of 200 trials = (√200) x 0.4 = 5.66
Therefore achieving a substantial increase in S/N ratio requires a very large increase in the number of trials.
So improve the quality of the data by decreasing the source of noise than by increasing the number of trials
61.
How many trials are a good number.
Practical suggestions
- 50 trials / condition / participant
- Similar number of trials for all conditions Phase/power produce positive bias with fewer trials)
- If not possible, match trial count
- Select the first N trials from each condition (N = the number of trials in the smallest condition)
- Select N trials at random
- Select N trials based on some relevant behavioural or experiment variable (i.e. reaction time)
62.
List the 4 ERP parameters.
- Latency (ms) (when is the peak reached?)
- Amplitude (μV) (what is the peak value?)
- Polarity (-/+) (is it positive or negative?)
- Distribution over the scalp (how are the electrodes distributed?
63.
Describe the use of Visual Evoked Potentials (VEP) in EEG research.
Presenting stimuli at intervals longer than a sec elicits a transient VEP
Presenting stimuli at faster rate elicit Steady State VEP (SSVEP)
- Provides fine grained information of early visual processing
- Routinely used to assess the integrity of the visual system from retina, via optic chiasm, to primary visual cortex
- Used in several clinical cases:
- Multiple sclerosis
- Visuospatial neglect patients
- Localization of optic lesions
64.
Describe the use of Auditory Evoked Potentials (AEP) in EEG research.
List:
- Early AEP,
- Middle latency Potentials
- Late Latency Potentials
1) Early AEP/ Brainstem AEP
- Testing the integrity of primary auditory pathways
- Localizations of deficits/damages
- Detection of early hearing loss in infants
2) Middle Latency Potentials
- 10 ms
- Possibly thalamic and very early cortical responses
- Earliest attention related effect (P1)
- Monitoring purpose in anesthetized conditions
3) Late Latency Potentials
- Cortical origin
- Reflect both the sensory processing and ongoing cognitive processing (i.e. attention)
- N1-P2 complex
- Developmental language disorders, dyslexia
65.
Describe the use of Somatosensory Evoked Potentials (SEP) in EEG research.
Various Sub-components
- Early N10 reflect action potentials from the peripheral nerves
- Subcortical (thalamic) components
- Cortical components for later latencies
Applications
- Tracking the somatosensory pathways from periphery to cortex
- Estimation of peripheral conduction velocities
- Patients with spinal chord injury, traumatic lesions, multiple sclerosis
- Classification of patients (i.e. apallic syndrome from locked-in states)
- Neuromonitoring purpose (spinal chord) during surgery
66.
Describe the use of Chemosensory Evoked Potentials in EEG research.
- Issue of timing
- No clear presence of early ERP components
- Amplitude is modulated by the concentration of odorant
- Useful for ageing study (olfactory discrimination degrades with normal ageing)
- Early detection of Alzheimers (olfactory impairment precedes cognitive impairment in AD)
67.
Describe the use of Contingency Negative Variation (CNV) in EEG research.
- Indicator of learning paired stimuli (Get Set – Go)
- Reflection of attention, concentration & readiness to S2
- Index of neuronal excitability
Interesting fact that if asked to move a finger the desision is activated subconsiously before we move - big implications on free will.
68.
N400 in Semantic Violations Kutas and Hilyard (1980) Science
A classic study where participants are exposed to semantically meaningless sentances.
When semantically wrong the N400 has a peak.
69.
Give some examples of Musical Semantics studies.
- Streit Quarrel Peace Ernest Bloch, (1880-1959) Duet for Cello and Violin
- Frieden Peace Quarrel J. S. Bach, (1685-1750) Cantata BWV 208
- D Schostakowitsch, (1906-1975) Arrival Departure Festival Overture, Op 69
- Ernest Farrar, (1885-1918) Departure Arrival
- English Pastoral Impressions, Op 26
70.
Music & Language: Semantical Priming Koelsch et al. (2004) Nat Neuro
Similar semantic priming effect in language and music
Medial temporal gyrus (neighbour to superior temporal sulcus STS)
- Center for semantic integration
N400 again implicated.
71.
Music: Rule Violation Koelsch et al (2000)
J Cogn Neurosci
- Music, like language, has “rules” – called syntax
- A listener expects specific musical events according to a preceding musical context
- Ex: Chord functions with final chord as regular (harmonically expected) or irregular (unexpected) Remember: The last chord itself is a valid musical entity, only the prior context makes the difference!
72.
Limitations of ERPs ?
- The first concerns interpretational issues, particularly with regard to interpreting null results
- ERP reveal little of EEG information
- ERP does not capture non-phase-locked responses
- The ERPs provide limited opportunities for linking results to actual neurophysiological dynamics
- ERPs are less understood compared to the neurophysiological mechanisms that produce neuronal oscillations and synchrony
73.
Dynamic Brain Oscillations
……………………….. have strict phase relationship to the stimulus
……………………. do not have strict phase relationship, Thus, ERP represents only ……………. not ………………..
Evoked oscillations have strict phase relationship w.r.to the stimulus.
Induced oscillations do not have strict phase relationship Thus, ERP represents only evoked activity not induced activity.
74.
Time-Frequency Representations:
What are the advantages?
- Clear interpretations
- Neurophysiological mechanisms
- Ubiquitous oscillations
- Neuronal oscillations are the most promising bridge linking findings from multiple disciplines
- Covers a more comprehensive multidimensional space
75.
Visual Feature Binding in Adults
Tallon-Baudry et al (1996) J Neurosci
Three stages: Illusionary triangle - real triangle and No-triangle.
76.
Visual Feature Binding in Infants
Csibra et al (2000) Science
77.
Oscillations in Complex Cognition
Sandkuhler, Bhattacharya (2008) PLoS ONE
78.
Neuronal precurser to Aha!
Posterior gamma for sudden solutions
79.
Time-frequency representation (TFR) Analysis: Limitations
- Decreased temporal precision
- Complicated analysis strategies
- Fewer previous research for contextualization of findings
- Does not provide information on the co-operation between brain regions
80.
Discuss Neuronal Synchrony.
- Cognition requires cooperation between neural populations within and across brain regions
- Synchronization of neural oscillations as a mechanism for integration of neural populations mediating perceptual binding and cognitive brain networks
- Neuronal assemblies that oscillate in synchrony exchange information more effectively relative to nonsynchronously oscillating assemblies
- Synchronization between multiple and distant brain regions
81.
Dense Brain Network in Musicians during Attentive Listening to Music
Higher Gamma Band Synchrony in Musicians
82.
Which EEG oscillation is most relevant for visual feature binding?
A.Alpha
B.Gamma
C.Beta
D.Delta
B Gamma?
One promising recent line of research has demonstrated a close association between gamma-band (‘40-Hz) oscillations of neural activity and visual binding, pointing to a central role for oscillatory neural circuits (Csibra et al., 2000)
83.
Measures of Synchronization
Pereda, Quiroga, Bhattacharya (2005) Progress Neurobiol.
Nonlinear Methods - what was found?
- Nonlinear correlation
- Information Theory
- Mutual Information
- Transfer entropy
- Phase Synchrony
- Hilbert +Shannon
- Mean phase coherence
- Wavelet
- Generalized Synchrony
- Similarity index & families
- Mixed predictability
- Cross prediction
84.
Which ERP component is associated with semantic violation in language?
A.MMN
B.P300
C.N400
D.N170
C.N400
85.
EEG: Some Open Issues
Experimental
- Choice of reference
- Volume conduction
- Relation between ERPs and Ongoing EEG oscillation
- Trial by trial variability
- Effect of pre-stimulus brain responses
Analysis
- Single trial analysis
- Synchrony in the source space
86.
Measures of Synchronization
Pereda, Quiroga, Bhattacharya (2005) Progress Neurobiol.
Linear Methods - what was found?
- Linear Correlation
- Coherence –Magnitude squared coherence
–Partial coherence
- Granger causality
- Multivariate modeling –Directed transfer function
–Partial directed coherence
