1 Neural Correlates of Cognitive Performance The brain is a complex of widely and reciprocally interconnected systems and the dynamic interplay of neural

1

Neural Correlates of Cognitive Performance

The brain is a complex of widely and reciprocally interconnected systems and the dynamic interplay of neural activity within and between these systems is the very essence of brain function

Mountcasle 1979

M. Doppelmayr, W. Klimesch

Conjunct COST B27 and SAN Scientific Meeting, Swansea, UK, 16-18 September 2006

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Overview

• Brief definition of the terms „Cognitive Performance“ and „Neural correlates“

• Structural differences• ERP-Results• Differences in Power (Amplitude) and Alpha-Peak-

Frequency (IAF)• Difference in the amount of the ERD

in the Upper Alpha and Theta bandNeural Efficiency Hypothesis, Inhibition Hypothesis

• Conclusions • Preview

Overview

Definitions

Structural Differences

ERPPowerERD Neuronale Effizienz vs. Inhibition Hypothesis

Conclusion

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Cognitive Performance

Intelligence, Working Memory Processes, Memory in general

Most results focussing on the relation between intelligence and EEG are based on typical intelligence tests as LGT 3 (Bäumler), CFT-3 (Cattell und Weiss 1971), IST-70 (Amthauer 1970), IST-2000 (Amthauer et al. 1999), RAVENS (RAVEN 1998), WILDE Intelligence Test (Jäger und Althoff 1994) or subtests of these and similar testsor different parameters of memory capacity

Baddeley A. (2003)Working Memory System:

Tulving E.: (1983)Elements of episodic Memory: semantic vs. episodic memory

Overview

Definitions


ERPPowerERD Neuronal Efficiency vs. Inhibition Hypothesis

Conclusion

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„Neural Correlates“

• Structuraldifferences

• Number / Volume of gray or white matter

as measured by means

of CT, MRI, Lesion- studies Post mortem etc.

• Differences in the activity of neurons or cortical areas

• EEG, MEG, ECGfMRI, NIRSPET, SPECT

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• Total brain volume correlates positive with general intelligence (g).Gignac et al. (2003) r = 0.40.

gray matter white mattertemplate template

• Haier et al. (2004) Sig. Correlationen of gray and white matter with WAIS (full scale FSIQ).More pronounced positive correlation with gray matter, with strongest effects at frontal, temporal and occipital areas N = 47

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Intelligence related differences in neural (EEG) activity

Correlation: String length of ERP and intelligence (WAIS) (Review Batt et al. 1999)

P

AN

AT

AN-P

AT-P

AT-AN

ZEIT 0 100 200 300 400 500 600 700

negative correlation p < 0.05

positive correlation p < 0.05

VIQ

P

AN

AT

AN-P

AT-P

AT-AN

ZEIT 0 100 200 300 400 500 600 700

PIQ

P = passive listening, AN Active response - NON targetsAT Active response - targets

Pz

2 µV

µV

time

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Different methods for analysis

ERPs String length

Pz

2 µV

time

Am

plit

ud

e

Pz

2 µV0 2 4 6 8 10 12 14 16 18 20 22 [Hz]

Frequency

Am

plit

ud

e/P

ow

er

Powerspektra

Co

he

ren

ce

Coherence

-5.0 µV 5.0 µV0 µV

2

4

6

8

10

12

14

16

18

20

22

24

26

28

30

32

34

36

38

[Hz]

-4.0 -3.5 -3.0 -2.5 -2.0 -1.5 -1.0 -0.5 0.0 [s]

C3

timeCh

an

ge

s in

am

plit

ud

e

ERDERSWavelets

Source Localization Phase-Locking

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ERP Resultsusually stimuli without specific meaning are presented

Pz

2 µV

µV

time

In general ERP- latencies are shorter for more intelligent subjects

Pz

2 µV

µV

time

ERP components have higher amplitudes in more intelligent subjects

Jausovec & Jausovec (2000)Widaman et al. (1990)Johnson et al. (1995)

Doppelmayr et al. (2000)Gevins & Smith (2000) Stauder et al. (2003)

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Alpha Power (Amplitude)and intelligence

Doppelmayr 2002

• Intelligenz-Struktur-Test Amthauer, R. (1970).

• Complete a sentence • Find a correct word• Analogies• Find similarities• Calculation task• Complete a number

sequence• Figure - template

matching• Mental rotation task• Memory task

• Lern-u. Gedächtnistest Bäumler, G. (1974).

• Learn and recall

a Mapturkisch vocablesobjectstelephone numbersspecific signs

Pz

2 µV0 2 4 6 8 10 12 14 16 18 20 22 [Hz]

AmplitudePower

• 3 min rest with eyes closed

• IQ test followed EEG recording

• 74 Vpn out of 89

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Conclusion

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PowerµV2

0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 Hz

5

10

15P4 High IQP3

P4 Low IQP3

Lower- 1 Lower-2 Upper Alpha Alpha Alpha

More intelligent subjects exhibited a significantly higher alpha power (6-12 Hz)

Doppelmayr et al. (2002)

Similar results have been reported by Klimesch et al. 1990, 1993, 2000 und Vogt et al.1998with respect to memory performanceSchmid et al. 2002: Alpha Bandpower FSIQ WAIS r = 0.38, p<0.0001.Anokhin & Vogel 1996

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Correlations of IQ-scores with alpha band power, depending on test specifity

Lower- 1 Lower-2 Upper Alpha Alpha Alpha

* **** ****

********

** ****** **

** **

* * * *

* * * * *

* *

****

LGT-30.50.40.30.2

** **

** **

**

**

* * *

*

IST-700.50.40.30.2

IQ-tests based on attention and STM abilities show positive correlations with powerestimates in all three alpha-bandsTests addressing selectively semantic memory, correlate positively only with upper alpha power

Doppelmayr et al. (2002)

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Neural activity during actual cognitive performanceOrigin of the neural "efficiency hypothesis“

Haier et al. (1988)

Negative correlation of PET activity and RAMP – Scores no topographically restricted effects

VpIQ-

VpIQ+

PET-Scansmicromol/glucose/100g brain tissue/minute

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Pz

S 71 S 82

100 µV

Pz

S 71 S 82

100 µV

1 Sek

Rawdata

Filtered data 10-12 HzReference Test

Pz

S 71 S 82

50 µV

Rectified (or squared)

Average Amplitude

7,5µV

2,5µV

ERD 65,7%

ERD-calculation Pfurtscheller & Aranibar 1977

4,0µV

45,2%

Synchronisation Increase

Desynchronisation Decrease100

500

-50-100

e.g.

100*.)(

)(.)(

REFPower

TESTPowerREFPowerERD

Pfurtscheller & Aranibar (1977)

Stimulus

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Conclusion

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Functional relevance of frequency bands

Pz

2 µV0 2 4 6 8 10 12 14 16 18 20 22 [Hz]

(Klimesch W. 1996, Klimesch W. et al. 1998, 1999, Doppelmayr et al. 1997,1998,2000)

0 2 4 6 8 10 12 14 16 18 20 Hz

ThetaAmplitude-increase

EpisodicMemory

Working Memory Processes

Lower-1 Alpha Amplitudedecrease

phasic alertness

Upper Alpha Amplitudedecrease

SemanticMemory

stimulus related processing.

Lower-2 Alpha Amplitudedecrease

reflects expectancy

Direction of changes during activation

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Conclusion

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Model of Klimesch (1997,1999)

Average performance

Referenz Test

60%

Referenz Test

80%

Referenz Test

30%

High performance

Weak performance

Alpha Range

Pow

er µ

V

ER

D

Klimesch et al. 2001

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Conclusion

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Referenz Test

40%

Referenz Test

70%

Referenz Test

30%

Pow

er µ

V

ER

S

20%

Average Performance

HighPerformance

WeakPerformane

Theta Range

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Conflicting theories about the amount of activity during task solving

• Stronger activity(Model proposed by Klimesch)

• Subjects with better memory performance exhibited a significantly stronger upper alpha ERD (=MORE ACIVATION) during semantic memory paradigms (Klimesch et al. 1997a,b, 1998…)

• Less activity Neural efficiency

• In a sentence verification task subjects with higher IQ scores exhibited a weaker upper alpha ERD (LESS ACTIVATION).Neubauer et al. 1995, Jausovec 1998

Neubauer et al., 1995Modified according Klimesch et al. 1997

Upper Alpha ERD in einer semantsichen Gedächtnisaufgabe

0

20

40

60

t1 t2

Zeit

ER

D% m+

m-

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ERD changes during solving of Raven matrices

Doppelmayr et al 2005

• 29 Subs. (6M, 23F)• Rest: 2 Min.• RAVEN SPM Intelligence-Test 60 Items – EEG recording• Rest: 2 Min.• Comparing Raven Scores to CFT-3 intelligence test;

Ref WS Onset TASK RT BLANK

2 0,5 1 2 to 60 Sek 8 Sek

Analysis-intervall 2 Sek. in the middle of the response time. Easy/difficult according to individual response timeonly correct answers analyzedERD according to ITV methodCFT-3 test scores correlated with the number of correctly solved RAVEN items r = +0,65Total = 119, IQ+ = 129, IQ- = 109RAVEN: IQ+ 51 correct, IQ- 43 correct

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Conclusion

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stimulus material 1

19

stimulus material 1

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Theta Band RAVEN

-15

-10

-5

0

5

IQ+ IQ-

ER

D% IQ+

IQ-

Results RAVENs3-fakt. ANOVA

IQ X TASK X LOC

IQ F(1,27)= 10.95; p < 0.01LOC F(4,108) = 8,71; p<0.001

IQ X TASK F(1,27)= 7,32; p < 0.05LOC F(4,108)= 8,26; p < 0.001

Upper Alpha Band RAVEN

0

5

10

easy difficult

ER

D% IQ+

IQ-

Thetamore pronounced Theta ERS for IQ+

Upper Alpha more pronounced ERD IQ- easy tasksIQ+ difficult tasks

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RAVENs-Results

• Theta:The neural efficiency hypothesis is insufficient to explain the results observed in the theta band because IQ+ showed significantly more activation (ERS).

• Upper Alpha:For the upper alpha band the neural efficiency hypothesis is valid only for easy tasks, not for tasks that are cognitively more demanding. Those matrices that are easy to solve, only by means of matching processes, but without any specific strategy can be explained by the neural efficiency hypothesis (weaker activation for IQ+).

• The fact that upper alpha is related to semantic memory might be a possible explanation for this contradictory findings (neural efficiency vs model of Klimesch).

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(Upper) Alpha Inhibition Hypothesis

• If for a specific task, semantic processing is required, then subjects with high IQ will show a more pronounced ERD = more activity (thus, in this case the neural efficiency hypothesis is incorrect)

• If, on the other hand, semantic processing is NOT necessary, thus, an activation of upper alpha useless or contraproductive, then this frequency band (upper alpha) will be inhibited or less activated by subjects with better performance (low ERD oder higher ERS – no difference to neural efficiency hypothesis).

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ERD in a verbal- semantic task:

AnalogiesDoppelmayr et al. 2005

67 items of IST-2000 and WIT34 Vpn (out of 50)ERD according to ITV basisCFT-3 Median Split to divide IQ+/IQ-IQ+ 50 correct, IQ- 45 correctCFT- 3 and number of correct answers r=0,49, p<0.05

Warning Signal500 Hz, 500 ms

TIME (ms)

0 ms

1000 ms

3000 ms

8000 ms

68000 ms

max. 1 Min. later Reaction

7000 ms Inter-Trial-Intervall

2 S

ek.

Ana

lysi

s in

terv

all

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Results verbal-semantic3-fakt. ANOVA

IQ X LOC X HEMISPHERE

Upper Alpha Band Aktivierung Verbal-Semantisch IQ

10

15

20

25

30

Fro Cen Tem PO Fro Cen Tem PO

ER

D-E

ve

nt-

rela

ted

De

sy

nc

hro

niz

ati

on

IQ-

IQ+

left hemisphere right hemisphere

Theta Band Aktivierung Verbal-Semantisch IQ

-20

-15

-10

-5

0

5

10

Fro Cen Tem PO Fro Cen Tem PO

ER

D-E

ve

nt-

rela

ted

De

sy

nc

hro

niz

ati

on

IQ-

IQ+

left hemisphere right hemisphere

IQ F(1,32)= 4,17; p < 0.05HEMI F(1,32) = 16,5; p<0.001LOC F(3,96)=11,86; p<0,001

More activity (neg ERD = ERS)for IQ+for the left hemisphere

LOC F(3,96)=11,86; p<0,001IQ X HEMI F(1,32)=5,97, p<0,05

More activity (positive ERD)for IQ+ in the left hemisphere

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Conclusion

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Summary of the „Inhibition Hypothesis“

• If, and only if, upper alpha activation is necessary and relevant for the solution of a given task, subjects with high IQ show a stronger activation in the relevant brain areas.

• If, on the other hand, upper alpha band is unrelevant, subjects with high IQ will actively inhibit this band (or at least show a weaker activation)

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Neural Efficiency Hypothesis is: contradicted in the theta band and

insufficient in the alpha band because:

• 1) In the theta-frequency band a stronger activation (ERS) has been reported repeatedly for more intelligent subjects.

• 2) In the upper alpha band in several (but not all) cases a stronger activation has been reported for subjects with better performance (IQ+ or M+)

• 3) The neural efficiency hypothesis, thus, has been contradicted for the theta band, and proofed useful in the upper alpha only if no semantic memory processes were required.

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General Summary• Studies focussing on structural differences according to

intelligence („g“) yielded positive correlations between several brain areas, more pronounced for gray, as compared to white matter.

• ERP-results indicated that latency is negatively and amplitude of several components positively correlated with intelligence

• EEG-Power and IAF (individual alpha frequency): In general subjects with higher IQ-scores (or memory performance) exhibited higher power and a faster IAF.

• ERD-Results:

Alpha: If the alpha band is of functional relevance for the requested task (semantic content), participants with higher performance (IQ) show a stronger activation (Model Klimesch). Contrary, if this frequency band is not relevant IQ+ subjects will show a weaker activation – or inhibition (inhibition hypothesis). Theta: Subjects with higher performance show a stronger activation of the theta frequency as indicated by a stronger ERS.

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Conclusion

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• Several remaining questions:EEG / fMRI combinedSource LokalisationPartial or directed CoherencePhase-Locking

• Possible applications in NeurofeedbackHanslmayr et al. (2005)Klimesch, Sauseng, Gerloff (2003)Stroke patients

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Acknowledgements:P. Sauseng, W. Gruber, K. Hödlmoser, W. Stadler, T. Pecherstorfer, R. Freunberger, S. Hanslmayr

Thank you for your attentionOverview

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Conclusion

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Documents

1 Neural Correlates of Cognitive Performance The brain is a complex of widely and reciprocally interconnected systems and the dynamic interplay of neural