STARmap
Cell-type-specific population dynamics of diverse reward computations
Computational analysis of cellular activity has developed largely independently of modern transcriptomic cell typology, but integrating these approaches may be essential for full insight into cellular-level mechanisms underlying brain function and dysfunction.
We integrated spatially resolved transcript amplicon readout mapping (STARmap) with genetically resolved optical and electrical recording to link specific cellular populations to behavioral elements of reward seeking. We showed that habenular tyrosine hydroxylase-expressing (TH+) neurons learn and encode reward-predicting cues, LHb Tac1+ neurons encode negative reward outcomes, and MHb Tac1+ neurons integrate rewards with accumulation dynamics that are well described by a line attractor. Using an approach custom-modified for Ca2+ signals, we demonstrated nonlinear dynamical systems modeling of in silico behavioral sessions to computationally test alternative reward contingencies, and finally compared the model’s activity dynamics to experimentally measured dynamics in mice.
Together, this approach illustrated the combination of spatial and genetic cell typology information with dynamical systems computational modeling for elucidating the functional significance of neural populations in behaving animals.
Link to 2022 Cell article
Transcriptome mapping in the 3D brain
RNA sequencing samples the entire transcriptome but lacks anatomical information. In situ hybridization, on the other hand, can only profile a small number of transcripts. In situ sequencing technologies address these shortcomings but face a challenge in dense, complex tissue environments. Wang et al. combined an efficient sequencing approach with hydrogel-tissue chemistry to develop a multidisciplinary technology for three-dimensional (3D) intact-tissue RNA sequencing (see the Perspective by Knöpfel). More than 1000 genes were simultaneously mapped in sections of mouse brain at single-cell resolution to define cell types and circuit states and to reveal cell organization principles.
LINK to 2018 Science research article