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Table of contents
I Introduction
1 Measures of neuronal activity
1.1 Electrophysiology
1.2 Neuroimaging
1.3 Optical Imaging
2 Functional Organization of the Visual Cortex
2.1 Neuron as a Basic Processing Unit
2.2 Overview of the Visual System
2.2.1 Early Visual System
2.2.2 The Primary Visual Cortex
2.2.3 Higher Visual Areas
2.3 Mesoscale Organization at the Population Level in V1
2.3.1 Columnar organization of the cortex
2.3.2 Connectivity inside a column: Spanning the layers of the cortex
2.3.3 Connectivity between columns: Horizontal connections
2.3.4 Cortical Maps
3 Dynamics of Visual Cortical Activity
3.1 Coding strategies
3.1.1 Temporal vs. rate coding
3.1.2 Coding by synchrony
3.1.3 Propagation in a cascade
3.1.4 Sparse coding
3.1.5 Dynamics of inhibition and excitation in shaping neuronal responses
3.1.6 Dynamics of orientation tuning
3.2 Operating Regimes of the Visual Cortex
3.2.1 Variability of Neuronal Responses
3.2.2 Structure and Role of the “Cortical Noise”
3.3 Attractor States and Transient States
4 Analysis Approach for VSD Imaging
4.1 Composition of VSD Imaging Recordings
4.2 Denoising strategies
4.2.1 Conventional Methods for Denoising VSD Imaging Data
4.2.2 Statistical Methods for Source Separation
II Methodology
5 Experimental Setup and Data Analysis
5.1 Animal Preparation
5.2 Visual Stimulation
5.3 Data Analysis
5.4 Stimulus locked time-frequency analysis
III Results
6 Source Separation for Denoising of VSD Imaging Data
6.1 Introduction
6.2 Results
6.2.1 Blank Subtraction and Division on VSD Imaging Data
6.2.2 Source Separation on Raw Data for Denoising
6.2.3 Variations of the Denoising Model
6.3 Discussion
7 Source Separation for Dimensionality Reduction
7.1 PCA on Denoised Recordings
7.1.1 Stimulus selective and nonselective components revealed by PCA
7.1.2 Dynamics of Orientation Selectivity on a 3-Dimensional Principal Component Space
7.1.3 Anisotropies of the ring attractor
7.1.4 Orientation preference on the ring attractor compared to the orientation map
7.1.5 Detection of the Area 17/18 Border by PCA
7.2 ICA on Denoised Recordings
7.3 Discussion
8 VSD Imaging in Response to Stimuli with Different Statistics
8.1 Denoising of Long Recordings
8.2 Variability of Neural Population Activity
8.3 PCA on Natural Image Response
8.4 Discussion
IV Conclusion
