Single-cell optogenetics reveals attenuation-by-suppression in visual cortical neurons

Area of Science:

• Neuroscience
• Computational Neuroscience
• Systems Neuroscience

Background:

• Understanding how neurons process information is crucial for brain computation.
• Previous studies suggested nonlinearities in neuronal input-output functions under anesthesia or in vitro.
• How neurons transform inputs in vivo during natural activity remained unclear.

Purpose of the Study:

• To characterize the in vivo activation functions of cortical principal neurons in awake mice.
• To investigate how varying network activity influences neuronal responses to fixed inputs.

Main Methods:

• Utilized two-photon optogenetics to deliver controlled somatic inputs to cortical neurons in awake mice.
• Manipulated neuronal activity levels by presenting sensory stimuli.
• Measured neuronal spiking output in response to fixed optogenetic input under different activity states.

Main Results:

• Neuronal responses to fixed optogenetic input remained largely linear when neurons were excited.
• Responses to fixed input were significantly attenuated when neurons were suppressed.
• This suppression acts as a filtering mechanism, prioritizing inputs to non-suppressed neurons.

Conclusions:

• In vivo somatic neural activation functions are linear above the resting point and exhibit suppression.
• These findings align with activation functions used in modern machine learning.
• Neuronal activation functions dynamically filter sensory inputs, influencing how stimuli are processed based on the neuron's current activity state.