Dynamic adaptation in fly motion vision [Elektronische Ressource] / vorgelegt von Virginia L. Flanagin

Virginia Flanagin

Sujets

• Biologie

Informations

• Publié par: ludwig-maximilians-universitat_munchen
• Publié le: 01 janvier 2006
• Nombre de lectures: 24
• Langue: Deutsch
• Poids de l'ouvrage: 5 Mo

Extrait

Dynamic Adaptation in Fly Motion
Vision


Virginia L. Flanagin





















München 2006










Dynamic Adaptation in Fly Motion
Vision


Virginia L. Flanagin








Dissertation
zur Erlangung des Doktorgrades
der Naturwissenschaften (Dr. rer. nat.)
der Fakultät für Biol ogie
der Ludwig-Maximilians-Universität München


Angefertigt am Max-Planck-Institüt für Neurobiologie,
Abteilung ‚Neuronale Informationsverarbeitung’



vorgelegt von
Virginia L. Flanagin
aus Chicago, IL USA





München, den 01. Juni 2006


3


Ehrenwörtliche Versicherung

Ich versichere hiermit ehrenwörtlich, dass die Dissertation von mir selbständig, ohne
unerlaubte Beihilfe angefertigt ist.


Martinsried, den………………………
…………………………………………



Erklärung

Hiermit erkläre ich, dass ich mich anderweitig einer Doktorprüfung ohne Erfolg nicht
unterzogen habe.


Martinsried, den……………………..
………………………………………….







Erstgutachter: Professor Dr. Alexander Borst
Zweitgutachter: Professor Dr. Benedikt Grothe

Tag der mündlichen Prüfung: 20. Juli 2006

4
Table of Contents
TABLE OF CONTENTS .........................................................................................................................5
TABLE OF FIGURES.................................................................................................................................7
ABBREVIATIONS.....8
ABSTRACT............10
1 INTRODUCTION12
FLY VISUAL SYSTEM.............................................................................................................................13
Photoreceptors15
Lamina............18
Medulla...........19
The lobula complex .........................................................................................................................21
Lobula plate tangential cells ............................................................................................................21
ELEMENTARY MOTION DETECTION........................................................................................................24
General Principles ..........................................................................................................................24
Gradient-type detector.....................................................................................................................25
The Reichardt Detector Model .........................................................................................................27
Evidence for the Reichardt Detector .................................................................................................30
ADAPTATION.......................................................................................................................................32
Efficient information transfer ...........................................................................................................33
Automatic adaptation ......................................................................................................................36
H1-cell and adaptation....................................................................................................................38
The time course of adaptation ..........................................................................................................41
JUSTIFICATION......43
2 METHODS....45
EXPERIMENTS.......45
Preparation.....45
Electrical Recording .......................................................................................................................47
Visual Stimulation...........................................................................................................................49
DATA ANALYSIS..................................................................................................................................54
Stimulus-Response Curves ...............................................................................................................55
Dynamic Gain.55
Cross-Correlation56
MODELING...........56
Visual Pattern..57
Motion Detector..............................................................................................................................58
TABLE OF EQUIPMENT AND SUPPLIERS....................................................................................................59
3 RESULTS .....................................................................................................................................61
DEPENDENCE ON STIMULUS STATISTICS.................................................................................................62
H1-cell firing properties ..................................................................................................................62
Stimulus-Response Function ............................................................................................................64
Dynamic Gain.67
5
Cross-correlations ..........................................................................................................................69
DEPENDENCE ON VISUAL PATTERN........................................................................................................71
TIME COURSE OF ADAPTATION..............................................................................................................77
4 DISCUSSION................................................................................................................................83
GENERALITY........84
Examples of automatic adaptation....................................................................................................84
Adaptation mechanisms in the Reichardt detector..............................................................................85
Adaptation of individual neurons and the Reichardt detector ..............................................................88
EFFICIENCY..........89
Efficient representations of correlations............................................................................................92
Ambiguity........93
DYNAMIC ADAPTATION IN MOTION DETECTION .......................................................................................94
VISUAL PATTERNS AND NATURAL SCENES ..............................................................................................97
FUNCTIONALITY IN THE FLY VISUAL SYSTEM ..........................................................................................99
Physiology of motion detection.........................................................................................................99
H1-cell functionality......................................................................................................................101
LPTCs network connectivity...........................................................................................................102
CONCLUDING REMARKS103
5 REFERENCES ...........................................................................................................................105
6 ACKNOWLEDGEMENTS111
7 CURRICULUM VITAE..............................................................................................................112
6
Table of Figures
Figure 1.1 Diagram of the fly visual system................................................................................... 14
Figure 1.2 Retinotopic organization in the fly visual system .......................................................15
Figure 1.3 Neural sup erposition and photoreceptor arrangement................................................16
Figure 1.4 Synaptic connections in a laminar cartridge................................................................18
Figure 1.5 Two proposed vision pathways in the fly. ...................................................................20
Figure 1.6 Diagram of 3 of the LPTC cell types............................................................................22
Figure 1.7 Two main classes of algorithmic motion detector models. .......................................25
Figure 1.8 The Reichardt m odel for directionally selective motion............................................28
Figure 1.9 Different versions of th e Reichardt motion detector. .................................................29
Figure 1.10 The motion energy model. ...........................................................................................30
Figure 1.11 The capacity for a neuron to m aximize information ................................................35
Figure 1.12 Adaptation to balanced background input. ..............................................................37
Figure 1.13 The anatomy of the H1-cell. ..................................................................