377-Jaxley: Simulation for Biophysical Neural Models

The paper introduces Jaxley, a novel differentiable simulation framework designed to bridge the gap between detailed biophysical neuron models and modern machine learning techniques. By utilizing JAX-based automatic differentiation and GPU acceleration, Jaxley allows researchers to optimize complex neural parameters—such as ion channel conductances and synaptic weights—using gradient descent rathe...去小宇宙查看完整单集简介
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