Probing Biological and Artificial Neural Networks with Task-dependent Neural Manifolds.
Michael KuochChi-Ning ChouNikhil ParthasarathyJoel DapelloJames J. DiCarloHaim SompolinskySueYeon ChungPublished in: CoRR (2023)
Keyphrases
- artificial neural networks
- biologically plausible
- feed forward
- neural network
- artificial neural
- bio inspired
- network architecture
- back propagation
- neural models
- biologically inspired
- spiking neural networks
- learning rules
- neural network model
- genetic algorithm
- mathematical modeling
- molecular biology
- neural model
- using artificial neural networks
- biological data
- biological systems
- low dimensional
- motor control
- genetic algorithm ga
- radial basis function
- neural fuzzy
- feed forward neural networks
- fuzzy systems
- manifold learning
- arbitrary dimension
- recurrent neural networks
- computational intelligence
- synaptic weights
- biological vision systems
- application of artificial neural networks
- evolutionary artificial neural networks
- endoscopic video
- high dimensional data
- visual cortex
- life sciences
- high throughput
- multilayer perceptron
- hidden layer
- euclidean space