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Orientation selectivity and the functional clustering of synaptic inputs in primary visual cortex

Abstract

The majority of neurons in primary visual cortex are tuned for stimulus orientation, but the factors that account for the range of orientation selectivities exhibited by cortical neurons remain unclear. To address this issue, we used in vivo two-photon calcium imaging to characterize the orientation tuning and spatial arrangement of synaptic inputs to the dendritic spines of individual pyramidal neurons in layer 2/3 of ferret visual cortex. The summed synaptic input to individual neurons reliably predicted the neuron's orientation preference, but did not account for differences in orientation selectivity among neurons. These differences reflected a robust input–output nonlinearity that could not be explained by spike threshold alone and was strongly correlated with the spatial clustering of co-tuned synaptic inputs within the dendritic field. Dendritic branches with more co-tuned synaptic clusters exhibited greater rates of local dendritic calcium events, supporting a prominent role for functional clustering of synaptic inputs in dendritic nonlinearities that shape orientation selectivity.

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Figure 1: Response properties of orientation-selective synaptic inputs to neurons in the ferret visual cortex.
Figure 2: Summed spine responses match somatic orientation preference, but are weakly orientation selective.
Figure 3: Location in orientation preference map reliably predicts somatic orientation preference but not somatic or synaptic input selectivity.
Figure 4: Nonlinear synaptic integration in visual cortical neurons.
Figure 5: Functional clustering predicts dendritic nonlinearities and somatic orientation selectivity.
Figure 6: Functional clustering and dendritic hotspots.

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Acknowledgements

The authors would like to thank the GENIE project for providing GCaMP6, D. Ouimet for surgical assistance, and G. Smith and W. Bosking for discussions. The research was supported by NIH grant EY011488 (D.F.) and by the Max Planck Florida Institute for Neuroscience.

Author information

Affiliations

Authors

Contributions

D.E. Wilson performed surgical procedures and two photon imaging, D.E. Wilson and D.E. Whitney performed intrinsic signal imaging, and D.E. Wilson and B.S. performed whole-cell recordings. All authors analyzed data. D.E. Wilson and D.F. wrote the paper with input from B.S. and D.E. Whitney.

Corresponding author

Correspondence to David Fitzpatrick.

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Competing interests

The authors declare no competing financial interests.

Integrated supplementary information

Supplementary Figure 1 Backpropagating action potential subtraction

(a) Example dendritic fluorescence trace; (b) Raw spine fluorescence trace plotted with predicted bAP component of spine signal; (c) Predicted synaptic signal after subtraction of predicted bAP.

Supplementary Figure 2 Examples of spine-isolated calcium transients

(a) Single calcium events occur and can be restricted to individual spines; scale bar 5 microns; (b) Responses recorded from four spines and adjacent parent dendritic branches illustrating that spine Ca2+ transients occur independent of dendritic events

Supplementary Figure 3 Precise alignment of two-photon imaging with intrinsic signal imaging

(a) Cranial window with two-photon FOV indicated by dashed white line, with control points indicated by red dots; Scale bar: 500 μm; (b) Intrinsic imaging orientation preference map; (c): Control point (red dots) placement guided by fiduciary markers; (d) Z-Projection of pia through 30 μm of two-photon z-stack; (e) Local orientation preference map.

Supplementary Figure 4 Spine orientation preference weakly matches map orientation preference

Comparison of single spine orientation preference with that of the spine’s location in the orientation preference map across all imaged neurons

Supplementary Figure 5 Computation of spine–soma input–output functions

Left column shows normalized summed spine responses with threshold applied; responses are aligned to the preferred orientation and Gaussian fit is shown as a dashed line; Middle column shows normalized somatic responses; responses are aligned to the preferred orientation and Gaussian fit is shown as a dashed line; Right column shows the spine-soma input output function, computed as interpolated fits of the spine input versus somatic output

Supplementary Figure 6 Spiking orientation selectivity is greater than Vm orientation selectivity

Comparison of spiking with subthreshold orientation selectivity; spiking and subthreshold measurements collected from each neuron are connected by a line

Supplementary Figure 7 Additional clustering analysis

(a) Nearest neighboring spines (n=765) show similar orientation preferences; (b) Apical(n=74) and basal (n= 72) dendritic branches show similar levels of circular dispersion; box boundaries are 25th and 75th percentile values and whiskers are maxima and minima; (c) The circular dispersion values for all branches on each cell are plotted against somatic orientation selectivity; each column of points is a single cell; cells ordered on the x-axis by their orientation selectivity; dashed line indicates cutoff for clustering;

Supplementary Figure 8 Hotspot data processing

(a) Example of isolated hotspot event without uniform dendritic activation; (b) Example of hotspot event before (black) and after (red) correction for uniform (putative bAP) dendritic contamination (dashed line); (c) Hotspot spatial size is not significantly different between events with small and large uniform dendritic activation; box boundaries indicate 25th and 75th percentiles, whiskers are minima and values adjacent to 1.5*IQR+75th percentiles

Supplementary Figure 9 Hotspots predict somatic orientation tuning

Summed spine, hotspot, and somatic tuning curves (dashed lines), spine-soma I/O functions (blue), and hotspot-soma I/O functions (red) for all imaged neurons, as in Supplementary Figure 5

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Wilson, D., Whitney, D., Scholl, B. et al. Orientation selectivity and the functional clustering of synaptic inputs in primary visual cortex. Nat Neurosci 19, 1003–1009 (2016). https://doi.org/10.1038/nn.4323

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