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
Hubel & Wiesel's Feedforward Model of Simple Cells
In the following successful model, we have 4 LGN neurons projecting on a particular simple cell in the cortex. Now, on the left we can see the receptive fields of the LGN cells, which happen to be aligned in space. Then, the receptive field of the simple cell will be maximally activated when the on-centers of the LGN cells are stimulated, which occurs when a properly oriented bar is presented. This model is accurate qualitatively, but not quantitatively. Indeed, it has been proven that orientation selectivity is enhanced also by cortical connections.
