Mapping of functionally characterized cell classes onto canonical circuit operations in primate prefrontal cortex

Area of Science:

• Neuroscience
• Computational Neuroscience
• Primate Neurophysiology

Background:

• Prefrontal cortex (PFC) microcircuits comprise diverse cell classes, but their specific roles in circuit operations during goal-directed behavior remain unclear.
• Distinguishing neuronal cell classes from extracellular recordings of action potentials presents a significant methodological challenge.

Purpose of the Study:

• To reliably segregate functional cell classes in the primate prefrontal cortex (PFC) during an attention task.
• To investigate how different cell classes contribute to canonical circuit functions within the PFC.

Main Methods:

• Developed an unbiased clustering protocol utilizing spike shape and neural firing variability to classify prefrontal cells.
• Recorded extracellular action potentials from macaques performing an attention task to analyze firing patterns.

Main Results:

• Successfully identified seven distinct functional cell classes: four broad spiking (BS) putative pyramidal cells and three narrow spiking (NS) putative inhibitory cells.
• Classified cells based on firing patterns: sparse/bursty, regular, or irregular, with varying synchronization to local field potential (LFP) oscillations (theta and beta bands).
• Observed distinct functional properties correlating with firing patterns, suggesting roles in flexible network activation, excitation-inhibition balance, and frequency-specific subnetwork tuning.

Conclusions:

• Spike shape and firing variability are reliable markers for distinguishing functional cell classes in the primate PFC.
• A limited repertoire of functional cell classes in the PFC supports both information representation and fundamental circuit operations during attentional engagement.