Notes
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A collection of fragments of understanding in the pursuit of deeper questions.
Contents
- Computational Vision
- Introduction to Data Science
- Translational Neuromodeling
- Deep Learning in Artificial & Biological Neuronal Networks
- Introduction to Neuroinformatics
- Intro to Neuroscience
- Systems Neuroscience
- Readings in Neuroinformatics
- Neurobiology of Consciousness
- Econometrics
- Principles of Finance
- Big Data & Databases
- Game Theory
- Intro to Blockchain
- Marketing Analytics
- Financial Accounting
- Fundamentals of Computer Science
- Foundamentals of Information Technology Law
- Statistics
- Computer Programming
- Macroeconomics
- EU Information Law & Data Economy
- Advanced Mathematics & Statistics
- Principles of Management
- Mathematics
- Microeconomics
Selectivity in V1 is Extremely Sharp
The grating at the center of the gratings' matrix here shows the optimal grating for a particular cell (specificity). All the gratings around it represent gratings to which the cell does not respond anymore. And we can see that just by changing the orientation a little bit (vertical axis), keeping the spatial frequency constant, the cell doesn't respond anymore. And the same can be observed in the opposite case (horizontal axis), where we change the frequency keeping the orientation constant.