Deep Learning

  1. How does human brain understand, process and learn that a human eye visualize?
  2. What are limitation of regular computer programs?
  3. What is Neural Networks/Deep Learning? What kind of problems does Deep Learning solve?

Visual Cortex of Human Brain:

The visual cortex of the brain is the area of the cerebral cortex that processes visual information received from the eyes. Complex mechanisms from retina to different visual areas allow us to read these lines. The visual system is inevitable for the way we interact with our surroundings as majority of our impressions, memories, feelings are bound to the visual perception. Visual area constitutes about 25 % of the cortex in humans with approximately 5 billion neurons. The study of the visual cortex has revealed many of these visual regions such as V1, V2, V3, V4 and MT on the basis of their anatomical architecture, topography and physiological properties [1]. These regions are involved in processing of multitude of informations (shape, orientation, color, movement, size etc) resulting from the visual pathways, thus making up an image applied to retina.


Computers and computing help us achieve more complex goals than a human alone. Despite, there are many goals that are beyond the scope of computing because of one major limiting factor, computers could only follow the specific instructions they were given. Solving problems with programming requires writing specific step-by-step instructions for a computer to follow. We call these steps; algorithms. This constraint limited the type of problems where computers could help us to those where we:

  1. Understand how to solve the problem
  2. Can describe the solution with clear step-by-step instructions that a computer can understand

Neural Network:

Limitation of traditional computer program and the structure of the human brain inspires a Neural Network to solve classification and detection problems. Neural Network is essentially a Machine Learning model (more precisely, Deep Learning) that is used in unsupervised learning. A Neural Network is a web of interconnected entities known as nodes wherein each node is responsible for a simple computation. In this way, a Neural Network functions similarly to the neurons in the human brain. More precisely Deep Learning allows computer to learn from examples.

  1. Identified a pattern within a problem
  2. Data that exemplifies the pattern


  1. Adaptation and Neuronal Network in Visual Cortex By Lyes Bachatene, Vishal Bharmauria and Stéphane Molotchnikoff. DOI: 10.5772/46011
  2. Felleman DJ, Van Essen DC 1991 Distributed Hierarchical Processing in the Primate Cerebral Cortex. Cereb Cortex. 1 147
  3. 1990, DeYoe EA, Olavarria J, Knierim J (1990) Modular and Hierarchical Organization of Extrastriate Visual Cortex in the Macaque Monkey. Cold Spring Harb Symp Quant Biol. 55 679696
  4. Essen DC, Zeki SM 1978 The Topographic Organization of Rhesus Monkey Prestriate Cortex. J Physiol. 277 193226 .
  5. 1992, Gadotti A, Cowey A (1992) Cortical Area 4 and its Role in the Perception of Color. J Neurosci. 12: 4056 EOF65 EOF.
  6. Born RT, Bradley DC 2005 Structure and Function of Visual Area MT. Annu Rev Neurosci. 28 157189
  7. MishkinM.UngerleiderL.Macko 1983 (1983) Object Vision and Spatial Vision: Two Cortical Pathways.Trends in Neuroscience. 6 414417 .
  8. Di CarloJ. J.ZoccolanD.RustN. C. 2012 How Does the Brain Solve Visual Object Recognition? Neuron. 73 415434 .
  9. MilnerD. A.GoodaleM.(1995 (1995).The visual brain in action. Oxford University Press



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