Unveiling the Future of AI: BINNs–Biologically Inspired Neural Networks

Monendra Grover, Dwijesh Mishra & Girish Kumar Jha


Biologically Inspired Neural Networks (BINNs) are a subset of artificial neural networks which derive inspiration from biological systems. There are several kinds of BINNs, as given below:

Spiking Neural Networks (SNNs): they derive inspiration from the behaviour of biological neurons, in which spikes or action potentials are used to transmit information. SNNs are used in neuroscience research to simulate biological neural activity. Our brains are complex, with many neurons and synapses connecting them. Traditional Artificial Neural Networks use continuous values for computation; in contrast, BINNs, like neurons, use discrete electrical impulses and spikes for transmitting information.

In ANNs (Artificial Neural Networks), continuous processing of input signals takes place. By contrast, in SNN, event-driven processing takes place each neuron accumulates input signals over time and generates an output spike after a certain threshold. Tasks like pattern recognition and synchronisation are relatively challenging for traditional ANNs. The precise timing of spikes is important for tasks mentioned above (such as pattern recognition…read more on NOPR