Laminar analysis of excitatory local circuits in vibrissal motor and sensory cortical areas

Abstract

Rodents move their whiskers to locate and identify objects. Cortical areas involved in vibrissal somatosensation and sensorimotor integration include the vibrissal area of the primary motor cortex (vM1), primary somatosensory cortex (vS1; barrel cortex), and secondary somatosensory cortex (S2). We mapped local excitatory pathways in each area across all cortical layers using glutamate uncaging and laser scanning photostimulation. We analyzed these maps to derive laminar connectivity matrices describing the average strengths of pathways between individual neurons in different layers and between entire cortical layers. In vM1, the strongest projection was L2/3→L5. In vS1, strong projections were L2/3→L5 and L4→L3. L6 input and output were weak in both areas. In S2, L2/3→L5 exceeded the strength of the ascending L4→L3 projection, and local input to L6 was prominent. The most conserved pathways were L2/3→L5, and the most variable were L4→L2/3 and pathways involving L6. Local excitatory circuits in different cortical areas are organized around a prominent descending pathway from L2/3→L5, suggesting that sensory cortices are elaborations on a basic motor cortex-like plan.

Figure 1. LSPS mapping in vM1, vS1, and S2.

(A) Schematic of vM1 location (inset, blue) with approximate plane of coronal section indicated (dashed line). Anterior is to the left, and lateral is at top. Adjacent low power brightfield image (left) shows coronal section of vM1. Higher power brightfield image (right) shows vM1 slice used for recording. White lines indicate approximate cytoarchitectonic laminar boundaries. No division was evident between L2 and L3 or L5B and L6 in motor cortex. (B and C) Similar presentation for location and laminar boundaries in vS1 and S2. Sensory cortical boundaries were sharper than those in motor regions. Boundaries in S2 are similar to vS1. (D) Overlay of 16×16 LSPS stimulus grid (blue dots) on image of vS1 slice, for mapping inputs to a L2/3 pyramidal neuron. (E) Examples of dendritic (gray) and synaptic (black) responses. Vertical lines indicate photostimulus timing (at 0 ms) and windows for dendritic response detection (7 ms) and synaptic responses (50 ms). (F) Example of LSPS map traces (boxed region in G). Gray traces: responses with dendritic component. (G) Example map from a L2/3 neuron. Pixels represent mean amplitude over synaptic window. Black pixels: dendritic responses.

Figure 2. Photoexcitability of presynaptic neurons.

(A) Excitation profile recorded from a L5B pyramidal neuron in vS1. Loose-seal recording was used to map the neuron's photoexcitable sites (grid: 8×8, 50 µm spacing, soma-centered). Central 4×4 region is shown. Circle: soma. Top of map is towards pia. Sites generating APs (green traces) were located peri-somatically. (B) Average excitation profiles for vM1 (left), vS1 (right), and S2 (bottom right) pyramidal neurons. Maps are soma centered. Bottom left, average vS1 excitation profile overlaid on slice image. (C) Number of APs per map per neuron, an estimator of the intensity of stimulation of neurons, plotted as a function of distance to pia. (D) Mean weighted distance from the soma of AP-evoking sites, an estimator of the resolution of stimulation of neurons, plotted as a function of distance to pia. For the grid used, the closest sites to the soma were at 35 µm. (E) Table summarizing excitability and spatial resolution for vM1, vS1, and S2.

Figure 3. Average vM1 input maps.

(A) Reconstructions of biocytin filled neurons in vM1. Neurons positioned according to radial distance (pia at top), and rotated to present the radial axis from pia to white matter as vertical. Axons not reconstructed. (B) Bright-field image of vM1, with overlaid LSPS grid (16×16 sites, 110 µm spacing), aligned to pia medially and superiorly. (C) Group-averaged input maps for neurons at different laminar depths. Normalized distances and approximate layers are indicated above the maps. Maps averaged by laminar depth in tenths (with no neurons in L1). Black pixels: dendritic response sites. Circles: somata. Points at map edges trimmed for display; color scale applies to all maps. Below, maps are averaged into groups of superficial (L2/3 and L5A) and deep (L5B and L6) neurons.

Figure 4. Average vS1 input maps.

(A) Group-averaged input maps for neurons at different laminar depths. Maps are averaged by layer. Normalized distances and layer boundaries are indicated above the maps. On rightmost map, markers are given to indicate position of laminar boundaries between cortical layers. Black pixels: dendritic response sites. Circles: somata. Points at map edges trimmed for display; color scale applies to all maps. (B) Maps are averaged by supragranular and infragranular position and presented as above. (C) Bright-field image of vS1, with overlaid LSPS grid (16×16 sites, 90 µm spacing), aligned to pia superiorly and centered over the neuron horizontally.

Figure 5. Average S2 input maps.

(A) Reconstructions of biocytin filled neurons in S2. Neurons positioned according to radial distance (pia at top, with lines spaced every 0.2), and rotated to present the radial axis from pia to white matter as vertical. Axons not reconstructed. (B) Bright-field image of S2 at right (lateral) end of vS1, with overlaid LSPS grid (16×16 sites, 90 µm spacing), aligned to pia superiorly and centered over the neuron horizontally. S2 maps are aligned such that the medial side (S1) is to the left, as indicated below the image. (C) Group-averaged input maps for neurons at different laminar depths. Normalized distances and approximate layers are indicated above the maps. Maps averaged by laminar depth in tenths (with no neurons in L1). On rightmost map, markers are given to indicate position of laminar boundaries between cortical layers. Black pixels: dendritic response sites. Circles: somata. Color scale applies to all maps. Below, maps are averaged into groups of supragranular, granular, and infragranular neurons.

Figure 6. Converting input maps to input vectors for connectivity matrices.

(A–D) Assigning coordinates of radial and horizontal distance to presynaptic locations in an input map: (A) Input map of a vM1 neuron. (B) Image of vM1 slice, overlaid with stimulus grid (blue dots), and radial spokes (yellow lines). Spokes were user-drawn along radial lines of the cortex. A central dashed spoke through recorded neuron's soma defines horizontal position h  =  0. These are used to measure stimulus grid locations (x, y) to transform them into (h, r) coordinates, where h is the horizontal arc distance (in µm) from the center spoke, and r is the normalized radial distance from the pia. Rainbow-like plots show interpolated maps of radial distance (C) and horizontal distance (D) for given points in an input map. (E–H) We selected points at a given presynaptic radial distance (two white boxes shown for adjacent superficial regions in E), within a limited horizontal range from the postsynaptic neuron. These regions were used to select points in the input map for binning purposes. By averaging the selected points in the input map at the given presynaptic depth (within the white boxes in F, for example), we converted input maps to input vectors (G). The postsynaptic radial distance for each recorded neuron was then used to place the input vectors in order, with vectors from superficial neurons in the top rows and deeper neurons in lower rows. By stacking the input vectors for every cell in a given cortical region, ordered by postsynaptic radial distance, a rough outline of the connectivity matrix can be presented (H).

Figure 7. Connectivity matrices for vM1, vS1, and S2.

(A, B, C) Connectivity matrices for vM1 (n  =  95 neurons). The input vector matrix (A) on left shows each neuron's input vector as a separate row, computed using the method in Figure 6. Rows are sorted by the normalized radial depth of the postsynaptic neuron's soma from L2/3 (top) to L6 (bottom). The white line indicates normalized radial depth for the given neuron in that row. Values given in pA per uncaging event, and binned by normalized distance from pia (1/14 of cortical depth, ∼90 µm). At middle, the neuron→neuron connectivity matrix (B) is given in pA per AP. Correction for presynaptic neuron density and number of APs (see Text S1) was applied to (A) to get the neuron→neuron connectivity matrix (B). White horizontal and vertical lines mark cortical layers; diagonal line marks within-layer connections. Top rows of the matrices (not shown) were empty, reflecting the absence of pyramidal neurons in L1. At right, the layer→layer connectivity matrix (C) is given in pA per AP per layer squared. Correction for presynaptic and postsynaptic neurons in each layer was applied to the neuron→neuron connectivity matrix (B) to derive the layer→layer connectivity matrix (C). This plot is binned by layer instead of by normalized distance from pia. (D, E, F) Connectivity matrices for vS1 (n  =  80 neurons). Left, individual neurons sorted as input vectors. Center, neuron→neuron connectivity matrix. Right, layer→layer connectivity matrix. (G, H, I) Connectivity matrices for S2 (n  =  100 neurons). Left, individual neurons sorted as input vectors. Center, neuron→neuron connectivity matrix. Right, layer→layer connectivity matrix.

Figure 8. Laminar wiring diagrams of three vibrissal-related areas.

(A) vM1. Using the neuron→neuron connectivity matrix, input-output wiring diagrams of cortical circuits are shown. Layers are indicated, with pia and superficial layers at the top, and neurons are divided into evenly spaced bins. Left, the strongest outputs at each bin. Only the single strongest projection from each bin is shown. Ascending pathways are shown on the left; descending connections on the right. Right, the strongest inputs at each radial depth. Only the single strongest connection to each bin is shown. Ascending inputs are shown on the left; descending inputs on the right. The arrow thicknesses indicate the relative strengths of connections. (B and C) Wiring diagram of vS1 and S2 displayed in similar fashion.

Figure 9. Quantitative comparison of neuron→neuron connectivity.

(A) Neuron→neuron pathway strength presented for vM1, vS1, and S2. Left, schematic of descending pathway from L2/3→L5. Cartoon is based on vS1 layers. Right, quantification (mean ± SD) of neuron→neuron pathway strength. Measurements of connection strength from input maps, of excitability in each cortical area, and of neuron density were resampled 10,000 times in a bootstrap analysis to determine variation (standard deviation). (B and C) Similar presentation for the ascending pathway from L6→L5 and L4→L2/3. For vM1, ascending input from L5A→L2/3 is presented in (C). (D) Quantification of all inputs to L5, presented on the same axis for comparison. (E) Quantification of all inputs to L2/3, presented on the same axis for comparison.