Quantitative analysis of electroencephalographic (EEG) signals
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Transcript of Quantitative analysis of electroencephalographic (EEG) signals
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Quantitative analysis ofelectroencephalographic (EEG) signals
www.epileptologie-bonn.de
Dept. of EpileptologyUniversity of Bonn
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•Quantitative EEG-methods: why?
•Example: Wavelet-based event-related potential (ERP)-analysis
•Phase-locking analysis of mediotemporal lobe (MTL) depth ERPs
•Declarative memory formation: MTL connectivity
•Summary
Quantitative EEG analysis
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Quantitative EEG methods: why?Example: sleep-EEG (qualitative)
Rechtschaffen and Kales, 1968
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Time
Hypnogram
Quantitative EEG methods: why?Example: sleep-EEG (qualitative)
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Quantitative EEG methods: why?Example: sleep-EEG (quantitative)
Electroencephalogr Clin Neurophysiol 1996; 98: 401-410
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Quantitative EEG methods: why?EEG = superposition of oscillations
Visual analysis: only low-frequency oscillations perception, cognitive processes!
1/f amplitude- characteristic
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Theta-gamma interaction within hippocampus
Chrobak u. Buzsáki, J. Neurosci. 1998
Interactions(hippocampus):
Theta (5Hz)
Gamma (>30Hz)
Quantitative EEG methods: why?
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Quantitative EEG methods: why?Event-related EEG: averaging
Average
event-related
potential (ERP)
Reduction of background „noise“: 1/n
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Quantitative EEG methods: why?
Averaged ERP-response ? ?
Amplitude-Changes Phase-Locking
Event-related EEG
evoked induced ( cognition)
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Wavelet-based ERP analysisTraditional approach: Fourier-transform
Power density
P () = F () F* ()
Spectral Coherence
Cxy() = |Pxy()|2 Pxx() Pyy()
Fourier-transform
F () = f(t) eit dt
Discrete: Fast-Fourier-transform (FFT)
f = 1 / T !
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Wavelet-based ERP analysisPhase-locking vs. amplitude-changes
Morlet-Wavelet: w(t,) = exp(-t2/22) * exp (it) Wavelet-Transform: W(t,) = f(t-) * w(,) d
Power (t,) = W(t,) 2 Phase (t,) = arctan (Im (t,) / Re (t,))
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Wavelet-based ERP analysis
Original EEG
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Phase-locking vs. amplitude-changes
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WT ERP-responses:
Wavelet-based ERP analysis
t,1Phases: t,2t,3 ...
Circular variance: | e i |
Shannon entropy: 1 + P log P
Histogram P():
-180 ° 0 ° 180 °
0°-180° 180°
Phase-locking vs. amplitude-changes
Variance?
Phase-locking index
e.g. Lachaux et al., Hum. Brain Mapp. 1999; Tass et al., Phys. Rev. Lett. 1998
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Brain region A
Brain region B
t,1 ? t,2 ? t,3 ? t,4 ?
Phase-synchronisation
Variance of phase differences t Synchronisation index
Wavelet-based ERP analysis
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Phase-locking analysis of MTL depth ERPsEpilepsy (prevalence 1%)
Seizures:
Unfamilar sensations
Unvoluntary body movements
Loss of consciousness
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Parahippocampal cortex
Rhinal cortex
Amygdala
Hippocampus
Phase-locking analysis of MTL depth ERPsMTL depth-recordings in epilepsy patients
MTL-epilepsy: 45% pharmaco-resistant
Presurgical evaluation: seizure focus?
Memory processes
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Phase-locking analysis of MTL depth ERPs
(neue Wörter)„Oddball experiment“: X ... X ... X ... O ... X ... X ... O ... X ... X
Hippocampus sclerosis Non-pathological side
Target Target
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Neuroimage 2005; 24: 980-989
Hippocampal P3
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Phase-locking analysis of MTL depth ERPs
Phase-locking
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Neuroimage 2005; 24: 980-989
Hippocampal P3: low-frequency range
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Phase-locking analysis of MTL depth ERPs
Phase-locking
Power
Hippocampus sclerosis Non-pathological side
Neuroimage 2005; 24: 980-989
Hippocampal P3: gamma range
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(neue Wörter)„Continuous recognition experiment“:
Haus ... Schiff ... Pferd ... Schiff ... Baum ... Haus ... Tisch ...
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Correct rejections (new)Hits (old)
OldNewNewNew New New
J. Cogn. Neurosci. 2004; 16:1595-1604
Phase-locking analysis of MTL depth ERPsAnterior mediotemporal lobe (AMTL)-N4
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J. Cogn. Neurosci. 2004; 16:1595-1604
Phase-locking
Power
( fMRI)
ERPs
(neue Wörter)(old words) (new words)
Phase-locking analysis of MTL depth ERPsAMTL-N4
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Declarative memory formation: MTL connectivityMTL depth electrodes
Interaction?
Declarative long-term memory: Consciously accessible information,
e.g. events and facts
Rhinal Cortex
Convergence of sensory data,semantic preprocessing Hippocampus
Synaptic plasticity, long term potentiation (LTP)
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•9 TLE patients with unilateral focus
•“Dm-effect” (difference due to memory):
remembered vs. forgotten words
Subsequent memory paradigm
Sahne
„Uhr“„Appetit“
„Sahne“„Ende“„Leistung“
„Mutter“
87
LearningLearning DistractionDistraction
?
Free recallFree recall
„84“„81“
„78“„75“
„72“. . .
Declarative memory formation MTL connectivity
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I I I I I I I I I II2000
µV– 20
400 1600120080020
ms
Rhinal cortex
Hippocampus
remembered
forgotten
Fernández et al., Science 1999
MTL-ERPs: “difference due to memory”
Dm-effects correlated (r = 0.92) rhinal-hippocampal interaction
Direct evidence?
-sync. coupling of assemblies
Declarative memory formation: MTL connectivity
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time [s]
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Change [%]: remembered - forgotten
Desynchronisation Synchronisation
Nat. Neurosci. 2001; 4: 1259-1264
Rhinal-hippocampal gamma synchronisationDeclarative memory formation: MTL connectivity
-180 ° 0 180 °
0°-180° 180°
Phase-synch. index:
remembered - forgotten
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Nat. Neurosci. 2001; 4: 1259-1264
Changes of gamma power
Rhinal cortex
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Changes of gamma power compared to baseline
Hippocampus
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Declarative memory formation: MTL connectivity
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Interpretation
• Rhinal-hippocampal phase coupling initiates information transfer ( 100 ms poststim.)
• Information transfer after onset of rhinal dm-effect (ERPs, 300 ms poststim.)
• Phase decoupling terminates information transfer ( 1000 ms poststim.)
• Reduced gamma power: specific assembly activation, suppression of gamma “noise”
Declarative memory formation: MTL connectivity
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Memory-related theta-gamma cooperation
Sp
ectr
al co
he
ren
ce
[%
] b
etw
ee
nrh
ina
l co
rte
x a
nd
hip
po
ca
mp
us
0
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forgotten words
remembered words
delta1-4Hz
theta4-7Hz
alpha17-10Hz
alpha210-13Hz
beta113-16Hz
beta216-19Hz
Eur. J. Neurosci. 2003; 17: 1082-1088
"dm"-effect: Gamma-synchronization
-0,2 0,0 0,2 0,4 0,6 0,8 1,0 1,2 1,4
"dm
"-ef
fect
: The
ta-c
oher
ence
0,0
0,2
0,4
0,6
0,8
1,0
r = 0.80, p = 0.018
Non-specific increase of theta-coherence
Specific theta-gamma
interaction
Declarative memory formation: MTL connectivity
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Gamma activity: interactions with theta and action potentials
Chrobak u. Buzsáki, J. Neurosci. 1998
Interactions(hippocampus):
Theta (5Hz)
Gamma (>30Hz)
Spikes
Declarative memory formation: MTL connectivity
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Hebbian assembly formation
Correlated firing of pre- and postsynaptic neuron Increase of synaptic efficacy (1949)
Experimental validation:
• Long-term potentiation and depression (LTP, LDP)• Spike timing dependent synaptic plasticity (STDP)
Synchronized gamma activity: precise spike timing (t < 10 ms)
(z.B. Engel u. Singer, Trends Cogn. Sci. 2001; Fries et al., Nat. Neurosci. 2001)
Abbott u. Nelson, Nat.. Neurosci. 2000
Declarative memory formation: MTL connectivity
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Rhinal-hippocampal coupling during sleep
• Dreams are difficult to remember
• Unrecognized scene shifts
• Duration severely misestimated
Memory formation during (REM-) sleep reduced
(e.g. Hobson et al., Behav. Brain Sci. 2000)
Sleep recordings in 8 unilateral MTLE patients
(Indirect) electrophysiological correlate?
Declarative memory formation: MTL connectivity
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Rhinal-hippocampal coupling during sleep
Eur. J. Neurosci. 2003; 18: 1711-1716
Declarative memory formation: MTL connectivity
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Rhinal-hippocampal 40 Hz coherence
Awake
Stage 1
REM
Stage 2
SWS
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Eur. J. Neurosci. 2003; 18: 1711-1716
Declarative memory formation: MTL connectivity
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Memory formation during sleep
Direct correlate?
Awakenings from REM sleep: dream recall in 6 patients (good, 79.2%) vs. 6 patients (poor, 6.7%)
• No group differences in daytime memory performance
• Sleep: “spontaneous memory formation”, attention, volition, semantic processing
Core factor of declarative memory formation
Declarative memory formation: MTL connectivity
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EEG power within hippocampusDeclarative memory formation: MTL connectivity
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Rhinal-hippocampal EEG coherenceDeclarative memory formation: MTL connectivity
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Rhinal-hippocampal connectivity
= core factor of
declarative memory formation
Declarative memory formation: MTL connectivityConclusion
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Summary
Quantitative EEG-analysis
•EEG = superposition of functionally specific oscillations
•Averaged ERPs = phase locking + amplitude changes
•Connectivity may be more relevant than amplitudes of local activations
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Guillén Fernández
Peter Klaver
Christoph Helmstädter
Thomas Dietl
Rüdiger Köhling
Edgar Kockelmann
Martin Lutz
Wieland Burr
Hakim Elfadil
Mario Städtgen
Carlo Schaller
Christian E. Elger
Kontakt: [email protected]
Dept. of EpileptologyUniversity of Bonn
www.epileptologie-bonn.de