neural-receptive-fields-hyperbolic-geometry

Receptive fields emerge naturally from the hyperbolic geometry of scale-free networks by embedding the network into hyperbolic space and mapping stimulus boundaries. This geometric approach produces localized neural activity patterns without requiring synaptic fine-tuning.

Yes, hyperbolic network embedding supports modeling both orientation selectivity and hippocampal place fields. The framework predicts degree-dependent receptive field sizes and accommodates multiple neural modalities through stimulus-space boundary mapping.

Initialize a scale-free network, apply hyperbolic embedding to model neural organization, map the stimulus space to the network boundary, then run rate-based or spiking neural dynamics simulations to observe receptive field formation.

Yes, the hyperbolic brain modeling framework is compatible with both rate-based and spiking neuron dynamics simulations. This flexibility allows researchers to study receptive field formation across different levels of neural modeling abstraction.

Hyperbolic geometry provides a physio-grounded framework where receptive fields arise from network structure itself, eliminating the need for synaptic fine-tuning. The hyperbolic embedding of scale-free networks naturally generates degree-dependent receptive field sizes.