Observing hidden neuronal states in experiments.

Area of Science:

• Neuroscience
• Computational Biology
• Electrophysiology

Background:

• Electrophysiologically active cells exhibit complex dynamics crucial for neural function.
• Understanding neuronal steady states and bifurcations is key to modeling brain activity.
• Existing methods often struggle to access hidden dynamical states in neurons.

Purpose of the Study:

• To develop a general experimental protocol for constructing steady-state bifurcation diagrams in electrophysiologically active cells.
• To validate computational models by exploring previously inaccessible regions of neuronal phase space.
• To experimentally verify the slow-fast dissection method in neuronal modeling.

Main Methods:

• Utilizing a voltage-clamp protocol as a closed-loop system to inform a subsequent current-clamp protocol on the same neuron.
• Employing a slowly ramped voltage-clamp to identify stable and unstable steady states.
• Analyzing transitions between steady and spiking states in the current-clamp phase.

Main Results:

• Demonstrated a method to experimentally determine steady-state bifurcation diagrams for entorhinal cortex neurons (excitatory and inhibitory).
• Validated the ability of the voltage-clamp to predict hidden steady states observed in current-clamp.
• Provided experimental support for the slow-fast dissection method in analyzing neuronal models.

Conclusions:

• The developed protocol enables model-independent construction of bifurcation diagrams, expanding model validation capabilities.
• This technique allows for the observation of complex hidden neuronal states.
• The approach facilitates precise control of neuronal behavior beyond traditional pharmacological methods.