Auditory cortical local subnetworks are characterized by sharply synchronous activity

Abstract

In primary auditory cortex (AI), broadly correlated firing has been commonly observed. In contrast, sharply synchronous firing has rarely been seen and has not been well characterized. Therefore, we examined cat AI local subnetworks using cross-correlation and spectrotemporal receptive field (STRF) analysis for neighboring neurons. Sharply synchronous firing responses were observed predominantly for neurons separated by <150 μm. This high synchrony was independent of layers and was present between all distinguishable cell types. The sharpest synchrony was seen in supragranular layers and between regular spiking units. Synchronous spikes conveyed more stimulus information than nonsynchronous spikes. Neighboring neurons in all layers had similar best frequencies and similar STRFs, with the highest similarity in supragranular and granular layers. Spectral tuning selectivity and latency were only moderately conserved in these local, high-synchrony AI subnetworks. Overall, sharp synchrony is a specific characteristic of fine-scale networks within the AI and local functional processing is well ordered and similar, but not identical, for neighboring neurons of all cell types.

Figure 1.

Waveform and connectivity analysis of pairs of neurons. A–C, Each column shows spike waveforms for a pair of recorded neurons. A, Waveforms for the two pairs. B, The sum of the two waveforms in A. C, The sum of the waveforms in B superimposed on the recorded neural trace. The estimated spike times for the pairs are shown below by the blue and red bars. D–G, Example cross-covariance functions. Waveforms for the two constituent neurons are shown in the plot. Scale bar, 1 ms. The direction of information flow in the cross-covariance function is shown by the arrow from one waveform to the other. Dashed lines in D–G, 99% confidence intervals. Solid lines in D, F, shift predictors.

Figure 2.

Population, laminar, and cell-type synchrony analysis. A, The time at which the peak occurred in cross-covariance functions (PD) was usually <4 ms, with the majority of peak delays <2 ms. B, PDs were similar in Supra, Gran, and Infra layers. C, The mean PDs across layers were <2 ms, with the shortest PDs in the Gran and Infra layers. D, HWs of cross-covariance functions were usually <2 ms. E, HW distributions across layers were similar. F, Mean HWs were consistent across layers, with the smallest HWs in Supra layers. G, CCC was broadly distributed. H, Supra pairs of neurons had the highest CCCs. I, Mean CCCs were highest in Supra and lowest in granular layers. J, Peak delays for FSU-RSU and RSU-RSU pairs were similar. K, Mean peak delays across the population and layer for different pairs of cell types (F-F: FSU-FSU; F-R: FSU-RSU; R-R: RSU-RSU). L, HWs of cross-covariance functions were small for FSU-RSU and RSU-RSU pairs. M, Mean HWs. N, CCCs for FSU-RSU and RSU-RSU pairs were similar. O, Mean correlation strength for the different pair types. *p < 0.05; **p < 0.01; ***p < 0.001.

Figure 3.

Example waveforms and STRFs. A–F, Each row represents two neurons recorded from the same electrode channel. Left: Example neuron spike waveforms. Middle and Right: STRFs corresponding to the spike waveforms. Depth of recording site and the average firing rate of each neuron are indicated above the STRF.

Figure 4.

STRF similarity for pairs of neurons. A, B, STRFs and STRF similarity for two example pairs of neurons. In A, the STRFs are moderately correlated, whereas in B, the STRFs are highly correlated. C, Population and laminar distributions of STRF similarities. D, Mean STRF similarities across layers. E, STRF similarity distributions for cell type pairs. F, Mean STRF similarity for cell type pairs. *p < 0.05; **p < 0.01; ***p < 0.001.

Figure 5.

BF, spectral tuning, and latency for pairs of neurons. A, Comparison between BFs. For each data point, the value on the abscissa corresponds to the neuron in the pair with the shortest spike waveform duration. B, Population BF differences, in oct. C, Mean BF difference versus layer. D, Q across the population of pairs. E, Spectral tuning differences, in oct. F, Spectral tuning differences across layers. G, Latency of peak in STRF. H, Latency differences. I, Latency differences versus layers. *p < 0.05; **p < 0.01; ***p < 0.001.

Figure 6.

Comparison between BF, spectral tuning, and latency of neighboring auditory cortical neurons of differing cell types. Comparison between BF, Q, and latency for FSU-RSU pairs (A–C), RSU-RSU pairs (D–F), and FSU-FSU pairs (G–I).

Figure 7.

Bicellular information analysis. STRF information for synchronous spikes was compared with that for each neuron in a pair. A, Bicellular information (information for synchronous spikes for each pair of neurons) compared with the maximum of the information values for the neurons in the pair. B–D, Bicellular versus maximum neuron information for Supra (B), Gran (C), and Infra (D) neurons. Bicellular information was higher for all comparisons (population: p < 0.001; Supra: p < 0.005, Gran: p < 0.001; Infra: p < 0.001; signed-rank tests). E, Information gain (bicellular information/maximum single neuron information). F, Information gain for cell-type pairs. *p < 0.05; **p < 0.01; ***p < 0.001.

Figure 8.

Summary of AI synchrony analysis. A, Comparison of connectivity parameters between different layers (columns 2–4) or between cell type pairs (columns 5–7). F-R, FSU-RSU; R-R, RSU-RSU; F-F, FSU-FSU. RF difference = 1 − STRF similarity. Circle size represents the relative magnitude of each parameter. Circles of different sizes represent significantly different values. Supra and Gran layers have closely matched laminar distributions. RSU-RSU pairs show the sharpest synchrony, whereas FSU-RSU pairs have the smallest receptive field differences. B–G, Bubble plots for synchrony and receptive field parameters for intralaminar (dark gray bubble, data from current study) and interlaminar (light gray bubbles; Atencio and Schreiner, 2010a) data. The title of each scatter plot indicates the parameter represented by the bubble. Bubble diameter is proportional to the parameter value. B, HW versus neuron separation. The smallest HWs occur for neighboring neurons, and these pairs of neurons have the highest STRF similarity. C, HW versus neuron separation shows that CCC is strongest for nearby, synchronously spiking neurons. D, E, Peak delay versus neuron separation, with STRF similarity and CCC indicated by bubble size. F, CCC versus neuron separation, with STRF similarity indicated by bubbles. G, STRF similarity versus neuron separation, with CCC indicated by bubbles. F and G also show data for putative monosynaptic interlaminar functional connectivity (dashed black lines).