Subgroups of parvalbumin-expressing interneurons in layers 2/3 of the visual cortex

Abstract

The input, processing, and output characteristics of inhibitory interneurons help shape information flow through layers 2/3 of the visual cortex. Parvalbumin (PV)-positive interneurons modulate and synchronize the gain and dynamic responsiveness of pyramidal neurons. To define the diversity of PV interneurons in layers 2/3 of the developing visual cortex, we characterized their passive and active membrane properties. Using Ward's and k-means multidimensional clustering, we identified four PV interneuron subgroups. The most notable difference between the subgroups was their firing patterns in response to moderate stimuli just above rheobase. Two subgroups showed regular and continuous firing at all stimulus intensities above rheobase. The difference between these two continuously firing subgroups was that one fired at much higher frequencies and transitioned into this high-frequency firing rate at or near rheobase. The two other subgroups showed irregular, stuttering firing patterns just above rheobase. Both of these subgroups typically transitioned to regular and continuous firing at intense stimulations, but one of these subgroups, the strongly stuttering subgroup, showed irregular firing across a wider range of stimulus intensities and firing frequencies. The four subgroups also differed in excitatory synaptic input, providing independent support for the classification of subgroups. The subgroups of PV interneurons identified here would respond differently to inputs of varying intensity and frequency, generating diverse patterns of PV inhibition in the developing neural circuit.

Fig. 1.

Lack of age dependence of membrane properties in parvalbumin-expressing (PV) interneurons in layers 2/3 of the visual cortex between postnatal day (P)15 and P19: average membrane resistance (R_m, A), action potential (AP) half-width (B), afterhyperpolarization (AHP) area (C), and input-output response (I/F slope, D) for each day of postnatal age (dpn). *Significantly different values (Tukey, P < 0.05). Error bars are ±SE.

Fig. 2.

Correlation of parameters describing membrane properties of PV interneurons. A: the 17 passive and active membrane properties used for clustering (derived from 82 interneurons; see materials and methods) are arrayed against each other in a correlation matrix with the degree of correlation indicated by the shading: white is uncorrelated (correlation index of 0) and black is perfectly correlated (correlation index of 1, diagonal squares). B: principal component analysis does not greatly reduce variance. For each principal component (PC) derived from the 17 PV interneuron membrane properties in A, the variance explained by that PC (eigenvalue, circles) and the cumulative proportion of variance explained by all PCs up to and including that PC (cumulative proportion, line) are plotted.

Fig. 3.

PV interneurons grouped with Ward's hierarchical clustering algorithm. Ward's hierarchical clustering was performed with 17 descriptive parameters of passive and active membrane properties (see materials and methods) derived from 82 interneurons. A: cell cluster merge heights were used to construct the dendrogram. Branch points (marking the formation of a new cluster from 2 smaller parent clusters) of heights >5.5 are labeled with cluster identities (unique numbers assigned when each cluster is created). All clusters converge at 36 arbitrary units (a.u.). The horizontal dashed line shows the best cut height, 17 a.u. Clusters below the best cut line are 63, 76, 77, and 78. B: the silhouette index is shown for each interneuron in the subgroups identified with Ward's clustering after a cut at the best cut line (k = 4). Positive values indicate a good cluster assignment, whereas negative values point to an interneuron that better fits an alternate cluster. Interneurons are shaded black (cluster 63), dark gray (cluster 76), gray (cluster 77), and light gray (cluster 78). Interneurons are ordered by silhouette index within each cluster and do not correspond to the order of interneurons displayed in the dendrogram in A.

Fig. 4.

Subgroup assignment of PV interneurons with k-means clustering. k-Means clustering was performed with the same data set as Ward's clustering. A: cluster assignments are depicted in a heat map in which each column represents 1 interneuron (n = 82) and each row contains the shaded k-means cluster assignment for k = 2 through k = 6. B: the silhouette index is plotted for each interneuron in each cluster generated by k-means clustering for k = 4. Interneurons are shaded black, dark gray, gray, and light gray, corresponding to the major clusters in A. As in Fig. 3B, interneurons are ordered by silhouette index within each cluster and do not correspond to the order of interneurons displayed in the heat map in A. C, top: the k-means cluster assignments for k = 4 (top) are depicted with the best cut cluster assignments from Ward's clustering (bottom). Cells clustered differently between the 2 methods are labeled. The 4 major k-means clusters are labeled with the corresponding subgroup identity; PV1a, PV1b, PV2, and PV3. C, bottom: the k-means cluster for k = 5 (top) is depicted with the cluster assignments from Ward's dendrogram cut at k = 5 (bottom), illustrating the further subdivision of PV3 into 2 subgroups.

Fig. 5.

Separation of subgroups in scatterplot of first 2 PCs. The first (PC1) and second (PC2) PC values derived for each interneuron are plotted against each other and shaded by k-means cluster (PV1a, PV1b, PV2, and PV3). Subgroups of interneurons are shaded black (PV1a), dark gray (PV1b), gray (PV2), and outlined light gray (PV3).

Fig. 6.

Membrane properties of PV interneuron subgroups in layers 2/3 of the visual cortex: AP firing patterns from representative interneurons from PV1a, PV1b, PV2, and PV3 subgroups (left to right). A: near-rheobase voltage traces contain ∼10 APs. PV1a interneurons typically jumped from no or a few APs to much higher frequencies (>25 Hz). The representative PV1a cell jumps from no to 30 APs, so the trace immediately before the 30 AP trace is shown. B: voltage traces (from the same cell shown in A) containing ∼30 APs. C: 1-s depolarizing currents injected into current-clamped PV interneurons generating the traces shown in A and B. The rheobase current is also shown for comparison if different from the stimulus trace for A and B.

Fig. 7.

First AP evoked at rheobase in each PV subgroup. A: the first AP firing in response to rheobase current is shown magnified to 10 ms. Shading and line thickness are coded by subgroup, for use in interpreting B and C. Rheobase stimulus for the records shown is 677 (PV1a), 280 (PV1b), 330 (PV2), and 190 (PV3) pA. B: the traces shown in A are overlaid, with 0 mV used to align them vertically. C: the traces shown in A are scaled to the same Max and Min, then overlaid.

Fig. 8.

Miniature excitatory postsynaptic current (mEPSC) characteristics of PV interneuron subgroups. A: representative current traces from each subgroup (10 s total time shown) in whole cell voltage clamp (holding potential −70 mV) in the presence of Mg²⁺, tetrodotoxin (TTX), and bicuculline (top traces) or in the same solution but with added 6-cyano-7-nitroquinoxaline-2,3-dione (CNQX, middle traces). The bottom 2 traces (100 ms each) are expanded from the top trace to show details. B–E: cumulative histograms (top) and mean values (bottom) of mEPSC amplitudes (B), 10–90% rise time (C), half-width (D), and frequency (E) for each subgroup. See materials and methods for details. For cumulative histograms, the Komogorov-Smirnov test finds significant differences between subgroups for each parameter (P < 0.05). *Significantly different values (Tukey, P < 0.05). Error bars are ±SE.