Thomas Lukasiewicz

Predictive dendrites as a foundation for biological learning

This paper introduces a model where neurons adjust synaptic strengths to minimize somato-dendritic mismatch, enabling network learning and reproducing experimental observations of plasticity.

Inferring Neural Activity Before Plasticity: A Foundation for Learning Beyond Backpropagation

This paper introduces a new credit assignment mechanism called prospective configuration, showing it can enable efficient learning in biological contexts and replicate observed neural behaviors.

Recurrent predictive coding models for associative memory employing covariance learning

This paper proposes predictive coding models that implicitly learn covariance information for associative memory, unifying predictive coding and covariance learning in hippocampal networks.