Bridging Function, Connectivity, and Transcriptomics of Mouse Cortical Neurons

Bridging Function, Connectivity, and Transcriptomics of Mouse Cortical Neurons
The versatile and powerful functional properties of the brain are reflected in the neuronal activity patterns and
computations, and their evolution over time due to learning, homeostatic plasticity, and other processes. The
composition of brain circuits out of a large number of cell types, which may be defined by the characteristic
patterns of gene expression, and the intricate connectivity of these circuits are expected to be intimately
related to their functional properties.
However, the exact nature of these relationships is far from clear. The concept of a cell type itself, especially
when considered at a fine-grained level, with a hundred or more cell types in any given brain area, is under
active research in the community. A central question is whether and how transcriptomically-defined cell types
provide specific underpinnings for broader circuit properties, such as those expressed in anatomy – defined by
neuron’s location, morphology, connectivity – or in the functional types of neuronal activity in vivo.
The proposed project will address this question by investigating the links between molecular and anatomical
cell types to circuits and function in the mouse primary visual cortex (V1). We will connect the types of
functional visual responses in vivo with transcriptomic types via multiplexed fluorescence in-situ hybridization
(mFISH). Calcium imaging of neural activity will be carried out across the full cortical depth in V1, co-registered
with mFISH imaging of that tissue, and the transcriptomic types of the neurons will be determined, establishing
links between each neuron’s function and its type.
In parallel, we will use a unique functional connectomics dataset already obtained at the Allen Institute, in
which Electron Microscopy (EM) images are co-registered with in vivo imaging data from V1. These data will
permit us to map the functional properties of each neuron to its morphological type and connectivity
characteristics, resolved in the EM volume. The morphological type will, in turn, allow us to compare this
dataset with the transcriptomic types, using our earlier PatchSeq dataset, where triple-modality data of
morphology, intrinsic electrophysiology, and transcriptomics was obtained for individual neurons.
These data and analyses will be freely shared with the scientific community. We will provide a web-based
resource through the Allen Institute Cell Type Cards portal, linking across transcriptomic, morphological,
connectivity, and functional types in these datasets.
Thus, this project will uncover the relations between transcriptomic types, cortical circuit structure, and its
function, while providing a major resource for a broad spectrum of future studies in this area.

Grant Number: 5U01MH130907-04
NIH Institute/Center: NIH
Principal Investigator: ANTON ARKHIPOV