Voxel-scale tracer projection density does not predict short-latency spike links between mouse visual areas better than distance in two Allen Neuropixels datasets
Question: does the point-to-point axon density between two positions in mouse visual cortex, predicted from Allen anterograde tracer data, tell which cross-area unit pairs have a short-latency directed spike link? Approach: We made a 100 um flatmap kernel-regression model of visual-cortex projections from 289 Allen tracer injections (leave-one-out r of log density 0.88 at a 200 um kernel; 0.63 without position). For each directed cross-correlogram test between units in two of six visual areas, the model gave the predicted density D from the source unit position at the target unit position. Data: Allen Visual Coding Neuropixels (passive; 3.37 million tests, 5,921 links, 50 mice) and Allen Visual Behavior Neuropixels (task; 4.84 million tests, 33,831 links, 34 mice). We used Poisson models with absorbed fixed effects and mouse-clustered errors. Result: Without a distance control, D predicted links in Visual Coding (rate ratio 2.18 per 10-fold D, z = 4.97). A spline of inter-unit distance removed most of this association (1.22, 95% CI 0.92-1.62). In Visual Behavior, D had no association at any level of adjustment (main model 0.94, 0.77-1.16). Distance alone was a strong predictor in both datasets: the link rate at 3 mm was 0.19 and 0.13 of the rate at 0.5 mm. In five variants (strict links, wild-type tracers, kernels of 100 and 400 um), Visual Coding estimates were always above 1 (3 of 10 significant) and Visual Behavior estimates were always below 1. No pooled estimate differed from 1. The reverse-direction density was not a better predictor. Limitation: D is a model prediction at tracer resolution (injections of about 0.5-1 mm) from other animals. Probe placement limits the range of D. A CCG link is not proof of a monosynaptic connection.
connectome · mesoscale connectivity · topography · Neuropixels · cross-correlogram · functional connectivity · mouse visual cortex · Allen Brain Observatory · structure-function · null result · cortical flatmap
References
8- usesdoi:10.1038/s41586-020-03171-x
Allen Visual Coding Neuropixels data (Siegle et al. 2021).
- useshttps://portal.brain-map.org/circuits-behavior/visual-behavior-neuropixels
Allen Visual Behavior Neuropixels data.
- usesdoi:10.1038/nature13186
Allen Mouse Brain Connectivity Atlas tracer grids (Oh et al. 2014).
- usesdoi:10.1038/s41586-019-1716-z
Cre-line projection classes and hierarchy scores (Harris et al. 2019).
- usesdoi:10.1016/j.cell.2020.04.007
Allen CCFv3 and cortical streamline flatmap (Wang et al. 2020).
- doi:10.1162/netn_a_00066
Voxel-scale kernel-regression connectivity model (Knox et al. 2019); our model uses the same idea on the flatmap.
- doi:10.1177/1536867X20909691
Poisson regression with high-dimensional fixed effects (ppmlhdfe; Correia, Guimaraes and Zylkin 2020).
- https://alleninstitute.org/terms-of-use/
Terms of use for Allen Institute data.
Cited by
2 publicationsPublic catalog entries on Sciscape.
- In 57 mice, LFP Granger influence in visual cortex went from lower to higher anatomical areas in all bands from 3 to 120 Hz; beta was not a feedback band
Prior campaign test of short-latency spike links between mouse visual areas against tracer projection density.
- In 82 opto-tagged mouse visual cortex Neuropixels sessions, spike-train troughs confirmed rare Vip inhibition from slice data, but Sst-to-FS inhibition exceeded the slice prediction
Earlier campaign study of inter-area short-latency spike links in Allen Neuropixels data.