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Statistical analysis and modeling of neural data Lecture 17 Bijan Pesaran 12 November, 2007
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Statistical analysis and modeling of neural data Lecture 17 Bijan Pesaran 12 November, 2007.

Dec 20, 2015

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Page 1: Statistical analysis and modeling of neural data Lecture 17 Bijan Pesaran 12 November, 2007.

Statistical analysis and modeling of neural data

Lecture 17

Bijan Pesaran

12 November, 2007

Page 2: Statistical analysis and modeling of neural data Lecture 17 Bijan Pesaran 12 November, 2007.

Goals• Practical issues of spectral representation

• Spectral estimation problem

• Examples on real data

Page 3: Statistical analysis and modeling of neural data Lecture 17 Bijan Pesaran 12 November, 2007.

Spectral intuition

=tv

LFP Voltage +

Spectrum

pow

er

1/T

ntSpike times

=T

frequency

pow

er

Low High 0

Spikes

Field

Coherency

Page 4: Statistical analysis and modeling of neural data Lecture 17 Bijan Pesaran 12 November, 2007.

Fundamental concepts

• Positive and negative frequency

• Nyquist frequency – aliasing

• Rayleigh frequency

• Spectral density and power

ttk coscos

t cos

K even

K odd

dffS2/1

0

2 )(2

Page 5: Statistical analysis and modeling of neural data Lecture 17 Bijan Pesaran 12 November, 2007.

The spectral estimation problem

Consistency and bias

Page 6: Statistical analysis and modeling of neural data Lecture 17 Bijan Pesaran 12 November, 2007.

Example I: LFP spectrograms

• Estimation issues– Bias

• Narrow band• Broad band

– Variance

– Degrees of freedom

Page 7: Statistical analysis and modeling of neural data Lecture 17 Bijan Pesaran 12 November, 2007.

Example I: LFP spectrograms

• Confidence intervals– Chi2

• Assume Gaussian process

– Jackknife• Does not assume Gaussian process

Page 8: Statistical analysis and modeling of neural data Lecture 17 Bijan Pesaran 12 November, 2007.
Page 9: Statistical analysis and modeling of neural data Lecture 17 Bijan Pesaran 12 November, 2007.
Page 10: Statistical analysis and modeling of neural data Lecture 17 Bijan Pesaran 12 November, 2007.

Example I: LFP spectrograms

• Example recordingCue CueSaccade Saccade

Page 11: Statistical analysis and modeling of neural data Lecture 17 Bijan Pesaran 12 November, 2007.

Example I: LFP spectrograms

Periodogram – Single Trial Multitaper estimate- Single Trial, [5,9]

Page 12: Statistical analysis and modeling of neural data Lecture 17 Bijan Pesaran 12 November, 2007.

Periodogram – Single Trial

Multitaper estimate- Single Trial

Example I: LFP spectrograms

Page 13: Statistical analysis and modeling of neural data Lecture 17 Bijan Pesaran 12 November, 2007.

Example I: LFP spectrograms

Multitaper estimate- Single Trial [5,9]

Multitaper estimate- Nine Trials [5,9]

Page 14: Statistical analysis and modeling of neural data Lecture 17 Bijan Pesaran 12 November, 2007.

Example I: LFP spectrograms

Multitaper estimate- Single Trial

Multitaper estimate- Nine Trials

Page 15: Statistical analysis and modeling of neural data Lecture 17 Bijan Pesaran 12 November, 2007.

Example I: LFP spectrograms

Multitaper estimate- 95% Chi2

212~ dofS

Multitaper estimate- 95% Jackknife

Leave-one-out

Page 16: Statistical analysis and modeling of neural data Lecture 17 Bijan Pesaran 12 November, 2007.

Example I: LFP spectrograms

Time (s)

Fre

quen

cy (

Hz)

-0.5 0 0.5 1 1.50

50

100

5

10

15

20

25

Multitaper estimate- T = 0.5s, W = 10Hz

Time (s)

Fre

quen

cy (

Hz)

-0.5 0 0.5 1 1.50

50

100

150

5

10

15

20

25

Multitaper estimate- T = 0.2s, W = 25Hz

Page 17: Statistical analysis and modeling of neural data Lecture 17 Bijan Pesaran 12 November, 2007.

Example II: Spike rates, spectra and coherence

Auto-correlation fn Multitaper spectrum[8,15]

Page 18: Statistical analysis and modeling of neural data Lecture 17 Bijan Pesaran 12 November, 2007.

Example II: Spike rates, spectra and coherence

Cross-correlation fn Multitaper coherence9 trials, [8,15]

Page 19: Statistical analysis and modeling of neural data Lecture 17 Bijan Pesaran 12 November, 2007.

Example II: Spike rates, spectra and coherence

Multitaper coherence9 trials, [12,23]

Multitaper coherence9 trials, [8,15]