Paulo Aguiar

This paper transfers reinforcement learning policies from in silico neuronal networks to in vitro cultures to control neuronal activity efficiently.

This paper develops a neuromorphic framework for real-time detection and manipulation of hippocampal ripples in vivo, achieving low-latency and energy-efficient performance.

The paper tests asymmetric microchannel designs to promote unidirectional connectivity in cultured neuronal circuits and finds that the 'Rams' design achieves ~76% unidirectional connections and ~94% directional spiking activity.

This paper develops flexible microelectrode arrays (MEAs) for recording neuronal activity in 3D cultures, showing improved performance and scalability.

The paper shows that excitatory and inhibitory synapses are tightly balanced along dendrites in developing hippocampal neurons, with this balance declining as the neurons mature.

This paper introduces adaptive delayed feedback control (aDFC) to disrupt neuronal oscillations and shows it outperforms standard DFC in reducing network synchrony.

This study demonstrates that astrocytes respond to electrical stimulation with membrane voltage oscillations and calcium waves, similar to neurons, and these responses depend on stimulus amplitude.

BigNeuron benchmarks automatic neuron reconstruction algorithms using gold standard annotations and image quality metrics, showing that consensus methods outperform individual algorithms.

This paper develops a method to pattern neuronal circuits in vitro using nanoscale structures to guide synapse formation between isolated neuron groups.

The paper shows that EAPs and antidromic conduction occur in neuronal cultures and can depolarize the soma, suggesting functional roles in neuronal activity.

This paper introduces a memristor-based neuromodulation device that enables real-time adaptive control of in vitro neuronal populations by detecting specific activity patterns and modulating synaptic-like interactions.