Updating the standard neuron model in artificial neural networks
From their inception in the 1950s, artificial neural networks (ANNs) started using the so-called point neuron model then prevalent in neuroscience, hoping that this analogy would allow for a better emulation of brain function. Over the years the neuroscience literature has shown that the point neuron model is too simplistic to properly represent many fundamental neural processes; however, the standard neuron model in ANNs still remains the same. Here we substitute it by a very recent model of cortical cells and demonstrate through theoretical analyses and experimental results how, simply by using a more realistic neural unit element without augmenting the number of parameters, the resulti...
| Authors | Raul Mohedano, Thomas Batard, Erik Velasco-Salido et al. |
|---|---|
| Primary category | cs.NE |
| Published | 19 May 2026 |
| Last updated at source | 9 June 2026 |
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