Convolutional Neural Network CNN: When Does a Neuron “Fire”?

Discover the key conditions for neuron firing in both biological and artificial neural networks. Learn how action potentials are triggered when threshold values are reached, a concept central to understanding neural activation.

Question

Comparing the basic structure of Neural Network with human body, when the cell is said to be fired?

A. if potential of body reaches a steady threshold values
B. if there is impulse reaction
C. during upbeat of heart
D. none of the mentioned

Answer

A. if potential of body reaches a steady threshold values

Explanation

Cell is said to be fired if & only if potential of body reaches a certain steady threshold values.

In biological neural networks, a neuron “fires” when the sum of excitatory and inhibitory signals it receives surpasses a specific threshold. This process is known as an action potential. Here’s a detailed explanation:

Biological Neuron Firing

• Resting Potential: Neurons maintain a resting membrane potential due to the distribution of ions (e.g., sodium and potassium) across their membranes.
• Excitatory and Inhibitory Inputs: Signals received by the neuron are processed through its dendrites. These signals can be:
  • Excitatory: Increase the likelihood of firing by depolarizing the membrane.
  • Inhibitory: Decrease the likelihood of firing by hyperpolarizing the membrane.
• Threshold Potential: If the combined input signals cause the membrane potential to reach a critical threshold (typically around -55 mV), voltage-gated ion channels open, triggering an action potential.
• Action Potential: This is an all-or-nothing event where an electrical impulse travels down the axon, transmitting information to other neurons or muscles via synapses.

Artificial Neural Networks (ANNs) Analogy

In artificial neural networks, this concept is modeled using activation functions:

• Each artificial neuron calculates a weighted sum of its inputs.
• If this sum exceeds a predefined threshold (or bias), the neuron “activates” or “fires,” passing its output to subsequent layers in the network.

Why Option A is Correct

The firing of biological neurons depends on reaching a steady threshold value, which aligns with option A. This mechanism ensures that only significant stimuli trigger neuronal responses, preventing random or unnecessary activations. Other options do not accurately describe this process:

Option B: Impulse reactions occur after firing but do not define when a neuron fires.
Option C: Heartbeat rhythms are unrelated to neuronal firing.
Option D: Incorrect as option A explains the mechanism.

Understanding this principle is foundational for both neuroscience and machine learning, as it bridges biological processes with computational models like ANNs.

Convolutional Neural Network CNN certification exam assessment practice question and answer (Q&A) dump including multiple choice questions (MCQ) and objective type questions, with detail explanation and reference available free, helpful to pass the Convolutional Neural Network CNN exam and earn Convolutional Neural Network CNN certification.