Deciphering the building blocks of the macaque prefrontal cortical microcircuit - Abstract
Since Ramon y Cajal, neuroscientists have speculated that even the most complex brain functions might even-
tually be understood at the level of neuronal cell types and their connections. More recently, while we have be-
gun to understand the wiring principles of cortical microcircuit in rodents at the level of cell types, we are still in
infancy in understanding the circuit organization of the primate neocortex at the level of cell types and their
connections, slowing the progress toward a mechanistic understanding of complex cognitive capabilities char-
acteristic of primates. For instance, the dorsolateral prefrontal cortex (DLPFC) of the primate brain is the most
evolutionarily developed brain region that supports complex cognitive processes characteristic of primates,
such as reasoning, planning, and abstract thinking. However, we know little about the constituent cell types
comprising DLPFC circuit, how each cell type connects each other to form a functional circuit, and what circuit
components specific to this circuit endow it with superb computational capabilities for complex cognitive pro-
cesses. To fill in this knowledge gap, we scale up a cost-effective, interdisciplinary approach to macaque
DLPFC, aiming at identifying all its consitiuent cell types and decipher their connectivity rules, with emphasis
on highly diverse GABAergic interneurons. We propose to use multi-cell patch recordings, single-cell RNA
sequencing (scRNA-seq), novel and rapid viral GABAergic labeling, and machine learning to achieve two main
goals: 1) dissect macaque DLPFC microcircuit by generating a morphological taxonomy of cell types in DLPFC
and mapping their connections; and 2) derive transcriptomic signatures of morphologically defined DLPFC
neurons using Patch-seq method, a novel scRNA-seq protocol. We have demonstrated the feasibility and suc-
cess of this approach in mouse neocortex, and our preliminary data indicate no technical issue in applying this
approach to primates. Using multi-cell patch recordings, we will characterize electrophysiology and morphology
of thousands of neurons and map connections between tens of thousands of cell pairs from DLPFC. Using
Patch-seq method, we will combine patch recording with a novel/sensitive scRNA-seq method (Smart-seq2) to
simultaneously obtain electrophysiology, morphology and transcriptome from single neurons, which can further
substantiate cell type classification and identify novel molecular markers for each cell type. We will prioritize
our effort on superficial layers of DLPFC, but eventually scale up our efforts to all layers if time permits. At the
end, the project will uncover a high-resolution microcircuit blueprint of macaque DLPFC with each circuit com-
ponent identified by specific genetic markers. Such a comprehensive dataset will provide the essential ground-
work to design molecular tools for further functional dissection of the complex cognitive processes subserved
by PFC. From a clinical perspective, having reference transcriptomes and connectivity patterns for different cell
types in primate DLPFC will facilitate our understanding of the relationship between disease-associated genes,
cell types, and circuit deficits in neuropsychiatric diseases, schizophrenia in particular.