Udaya Bhaskar Rongala

A cortical-like network learns to process dynamic sensory inputs through autonomous learning, demonstrating robustness to sensor and connection removal.

This study models skin dynamics to improve tactile sensing by incorporating mass into mechanical models, enhancing the separability of tactile inputs.

The paper uses ECoG recordings and PCA to detect changes in global cortical activity distribution following tactile stimulation, showing sensitivity even without somatosensory cortex data.

The paper introduces a non-spiking neuron model with dynamic leak to assess stability in recurrent networks, finding it reduces spurious high-frequency noise and scales with network size.