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E-raamat: Handbook of Neural Activity Measurement

Edited by (Ecole Normale Supérieure, Paris), Edited by (Centre National de la Recherche Scientifique (CNRS), Paris)
  • Formaat: PDF+DRM
  • Ilmumisaeg: 06-Sep-2012
  • Kirjastus: Cambridge University Press
  • Keel: eng
  • ISBN-13: 9781139557771
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  • Formaat: PDF+DRM
  • Ilmumisaeg: 06-Sep-2012
  • Kirjastus: Cambridge University Press
  • Keel: eng
  • ISBN-13: 9781139557771
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"Neuroscientists employ many different techniques to observe the activity of the brain, from single-channel recording to functional imaging (fMRI). Many practical books explain how to use these techniques, but in order to extract meaningful information from the results it is necessary to understand the physical and mathematical principles underlying each measurement. This book covers an exhaustive range of techniques, with each chapter focusing on one in particular. Each author, a leading expert, explains exactly which quantity is being measured, the underlying principles at work, and most importantly the precise relationship between the signals measured and neural activity. The book is an important reference for neuroscientists who use these techniques in their own experimental protocols and need to interpret their results precisely; for computational neuroscientists who use such experimental results in their models; and for scientists who want to develop new measurement techniques or enhance existing ones"--Provided by publisher.

Arvustused

"The book is an important reference for neuroscientists who use these techniques in their own experimental protocols and need to interpret heir results precisely; for computational neuroscientists who use such experimental results in their models; and for scientists who want to develop new measurement techniques or enhance existing ones." -Mathematical Reviews

Muu info

Underlying principles of the various techniques are explained, enabling neuroscientists to extract meaningful information from their measurements.
List of contributors
ix
1 Introduction
1(7)
Romain Brette
Alain Destexhe
References
7(1)
2 Electrodes
8(36)
Thomas Stieglitz
2.1 Introduction
8(3)
2.2 Electrochemistry at electrodes
11(12)
2.3 Electrode types
23(10)
2.4 Reactions and processes at implanted electrodes
33(1)
2.5 Amplifiers and filters for extracellular and intracellular recording
34(7)
2.6 Conclusions
41(3)
References
41(3)
3 Intracellular recording
44(48)
Romain Brette
Alain Destexhe
3.1 Introduction
44(7)
3.2 Recording the membrane potential
51(16)
3.3 Recording currents
67(9)
3.4 Recording conductances
76(11)
3.5 Conclusion
87(5)
References
88(4)
4 Extracellular spikes and CSD
92(44)
Klas H. Pettersen
Henrik Linden
Anders M. Dale
Gaute T. Einevoll
4.1 Introduction
92(2)
4.2 Biophysical origin of extracellular potentials
94(6)
4.3 Local field potential (LFP) from a single neuron
100(7)
4.4 Extracellular signatures of action potentials
107(11)
4.5 Extracellular potentials from columnar population activity
118(5)
4.6 Estimation of current source density (CSD) from LFP
123(7)
4.7 Concluding remarks
130(6)
References
130(6)
5 Local field potentials
136(56)
Claude Bedard
Alain Destexhe
5.1 Introduction
136(3)
5.2 Modeling LFPs in resistive media
139(3)
5.3 Modeling LFPs in non-resistive media: general theory
142(7)
5.4 Modeling LFPs in non-resistive media: the continuum model
149(11)
5.5 Modeling LFPs in non-resistive media: the polarization model
160(11)
5.6 Modeling LFPs in non-resistive media: the diffusion model
171(4)
5.7 Synthesis of the different models
175(4)
5.8 Application of non-resistive LFP models to experimental data
179(5)
5.9 Discussion
184(8)
References
188(4)
6 EEG and MEG: forward modeling
192(65)
Jan C. de Munck
Carsten H. Wolters
Maureen Clerc
6.1 Introduction
192(1)
6.2 The current dipole model and the quasi-static approximation
193(12)
6.3 Analytical solutions
205(16)
6.4 The boundary element method
221(11)
6.5 The finite element method
232(12)
6.6 Other forward methods
244(1)
6.7 Discussion and conclusion
244(13)
References
248(9)
7 MEG and EEG: source estimation
257(30)
Seppo P. Ahlfors
Matti S. Hamalainen
7.1 Introduction
257(2)
7.2 Relationship between neural activity and the MEG and EEG source estimates
259(4)
7.3 Source estimation methods
263(7)
7.4 Interpretation of the source estimates
270(7)
7.5 Comparison with other techniques and future developments
277(10)
References
279(8)
8 Intrinsic signal optical imaging
287(40)
Ron D. Frostig
Cynthia H. Chen-Bee
8.1 Introduction
287(2)
8.2 Background and theory
289(11)
8.3 Relationship between intrinsic signals and underlying neuronal activation
300(5)
8.4 More on intrinsic signals in the rat barrel cortex
305(17)
8.5 Current trends and future directions
322(5)
References
323(4)
9 Voltage-sensitive dye imaging
327(35)
S. Chemla
F. Chavane
9.1 Introduction
327(1)
9.2 Voltage-sensitive dye imaging: basics
328(9)
9.3 On the origin of the VSD signal
337(4)
9.4 Models of VSDI signals
341(13)
9.5 Conclusion
354(8)
References
355(7)
10 Calcium imaging
362(48)
Fritjof Helmchen
10.1 Fluorescent calcium indicators
363(4)
10.2 Intracellular calcium dynamics
367(9)
10.3 Calcium-dependent fluorescence properties
376(9)
10.4 Simplified models of calcium dynamics
385(9)
10.5 Application modes
394(8)
10.6 Comparison with other techniques
402(1)
10.7 Future perspectives
403(7)
References
404(6)
11 Functional magnetic resonance imaging
410(60)
Andreas Bartels
Jozien Goense
Nikos Logothetis
11.1 Introduction
410(4)
11.2 Physical basis of the fMRI signal
414(3)
11.3 BOLD contrast mechanism
417(9)
11.4 Analysis of fMRI signals
426(12)
11.5 Neural basis of BOLD signals
438(17)
11.6 Conclusions
455(15)
References
456(14)
12 Perspectives
470
12.1 Extracellular recording
470(1)
12.2 Intracellular recording
471(1)
12.3 Local field potentials
472(1)
12.4 EEG and MEG: forward modeling
473(1)
12.5 EEG and MEG: source estimation
474(1)
12.6 Intrinsic optical imaging
474(1)
12.7 Voltage-sensitive dye imaging
475(1)
12.8 Calcium imaging
475(2)
12.9 Functional magnetic resonance imaging
477
References
477
Romain Brette is Associate Professor in the cognitive science department at the Ecole Normale Supérieure, Paris. Alain Destexhe is CNRS Research Director in the Laboratory for Computational Neuroscience, Gif-sur-Yvette.