Automatic signal adaptation for real-time bidirectional interaction with the nervous system

Manuel Reyes Sánchez

Director: Pablo Varona Martínez

May 2023

PhD thesis supplementary material

 


 

Hybrid circuit electrical coupling experiment

With both neurons in a compatible range, the conductance of the electrical synapse is gradually incremented.

The Mean Square Error is calculated in real-time. The target MSE is a percentage of the initial MSE.

When the target MSE is reached, the conductance stops increasing.

This way, electrical synchronization is achieved with the minimum amount of current injection.

Each channel audio corresponds to one neuron. When the target is achieved, both neurons fired together and thus sound, at the same time

 


 

The dynamical invariant in the living CPG

The developed algorithms detect the spikes and bursts in the signals from the living neurons.

With these events, the time intervals can be detected (red, blue and black lines)

In the right panel, we plot the LPPD interval and the delay against the cycle period.

The video corresponds to a 28 minutes experiment.

Each channel audio corresponds to one neuron. The antiphase behavior can be perceived in the audio (use headphones)

 


 

Hybrid dynamical invariant circuit using genetic algorithm

This video explains how the genetic algorithm manages to reproduce the dynamic invariant in a hybrid circuit.

 


 

Video of the hybrot locomotion controlled by the living CPG

When the robot is in a shadow zone, it is detected by the sensors

This injects a feedback signal in the living circuit that changes the frequency of the cycles

This effect can be seen in the neuron signal on the screen