2.1 Bio Inspired Learning

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 Bio-inspired Learning: -

  • The term "Artificial Neural Network" is derived from Biological neural networks that develop the structure of a human brain, Similar to the human brain that has neurons interconnected to one another.
  • Bio-inspired learning means designing machine learning algorithms by taking inspiration from biological systems, especially the human brain and nervous system.

In biology:

  • Neurons receive signals

  • Process them

  • Pass signals to other neurons

  • Strengthen or weaken connections based on experience

In machine learning:

  • Artificial neurons receive inputs

  • Multiply by weights

  • Apply an activation function

  • Produce output

  • Update weights using learning rules

The most common bio-inspired model is the Artificial Neural Network (ANN).

  • Artificial neural networks also have neurons that are interconnected to one another in various layers of the networks. These neurons are known as nodes.


Parts and Their Functions

  1. Dendrites
    Receive signals from other neurons.

  2. Soma (Cell Body)
    Processes incoming signals.

  3. Nucleus
    Controls neuron activities.

  4. Axon
    Carries electrical signals away from the soma.

  5. Myelin Sheath
    Insulates the axon and speeds up signal transmission.

  6. Schwann Cell
    Produces the myelin sheath.

  7. Node of Ranvier
    Gaps between myelin segments that help speed up signal transmission.

  8. Axon Terminal
    Passes signals to the next neuron.



  • A Human brain has billions of neurons. Neurons are interconnected nerve cells in the human brain that are involved in processing and transmitting chemical and electrical signals.

        1) Dendrites are tree-like branches originating from a cell body. they receive information from the other neurons.

        2) Axon is a cable that is used by neurons to send information. Towards it end, the axon splits up into many branches that make connections with the other neurons through their dendrites or axon tips. Synapse is the connection between the axon dendrites or tips and other neuron dendrites.

        3) Soma or cell nucleus is the core of the neuron. it is responsible for processing the information received from dendrites.


This diagram shows how two neurons communicate.

Step-by-Step Explanation

  1. The first neuron receives signals through dendrites.

  2. The signal is processed in the cell body.

  3. An electrical impulse travels along the axon.

  4. At the synapse, chemical signals are released.

  5. The next neuron receives the signal through its dendrites.

This process continues across millions of neurons.

  • While transmitting information, the input signals (impulse) should be strong enough to cross a certain threshold barrier, then only a neuron activates and transmits the signal further (output).
  • Inspired by the biological functioning of a neuron, an American scientist Frank Rosenblatt came up with the concept of perceptron at cornell aeronautical laboratory in 1957.
  • He proposed that a neuron receives information from other neurons in the form of electrical impulses of varying strength.
  • Neuron integrates all the impulses it receives from the other neurons.
  • If the resulting summation is larger than a certain threshold value (a specific level value), the neuron ‘fires’, then an action potential triggered and transmitted to the other connected neurons.



Simple Example

Suppose you want to predict whether a student will pass an exam.

Inputs:

  • Study hours

  • Attendance

  • Previous marks

Each input goes into an artificial neuron (like dendrites).

The neuron:

  1. Multiplies each input by a weight

  2. Adds them

  3. Applies an activation function

  4. Produces output: Pass (1) or Fail (0)

That entire process is inspired by how the biological neuron works.

























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