Spatiotemporal dynamics of neocortical excitation and inhibition during human sleep

Abstract

Intracranial recording is an important diagnostic method routinely used in a number of neurological monitoring scenarios. In recent years, advancements in such recordings have been extended to include unit activity of an ensemble of neurons. However, a detailed functional characterization of excitatory and inhibitory cells has not been attempted in human neocortex, particularly during the sleep state. Here, we report that such feature discrimination is possible from high-density recordings in the neocortex by using 2D multielectrode arrays. Successful separation of regular-spiking neurons (or bursting cells) from fast-spiking cells resulted in well-defined clusters that each showed unique intrinsic firing properties. The high density of the array, which allowed recording from a large number of cells (up to 90), helped us to identify apparent monosynaptic connections, confirming the excitatory and inhibitory nature of regular-spiking and fast-spiking cells, thus categorized as putative pyramidal cells and interneurons, respectively. Finally, we investigated the dynamics of correlations within each class. A marked exponential decay with distance was observed in the case of excitatory but not for inhibitory cells. Although the amplitude of that decline depended on the timescale at which the correlations were computed, the spatial constant did not. Furthermore, this spatial constant is compatible with the typical size of human columnar organization. These findings provide a detailed characterization of neuronal activity, functional connectivity at the microcircuit level, and the interplay of excitation and inhibition in the human neocortex.

Fig. 1.

(A) Localization of subdural electrodes (SI Materials and Methods) and the NeuroPort electrode array (gray square in Inset). (B) Green traces show electrocorticogram (EcoG) of the four closest contacts to the microelectrode. LFP recorded from the NeuroPort is plotted in black. Raster plot shows the pooled firing of inhibitory (red) vs. excitatory (blue) cells for this period of slow-wave sleep. Histogram shows normalized neuronal firing rate for the two groups of cells in 200-ms time bins. (C) Total spikes by RS and FS cells in successive 200-ms bins, plotted against each-other (same epoch as in B).

Fig. 2.

Separation of FS and RS cells based on spike waveform. (A) Valley-to-peak and half-peak widths were the two parameters chosen to describe spike waveforms. (B) Each cell's average waveform is represented in the 2D space of the previous two parameters. The two clusters were identified with a k-means algorithm representing in red FS and in blue RS cells. (C) Average spike waveform for the two groups. Shading represents SD. (D) Probability density of firing rates for the two groups. (Inset) Average ± SEM. (E) Box plot indicating interquartile distribution of coefficients of variation (CV) of ISIs. (F) Average autocorrelogram normalized to maximum for each group. (G) Distribution of autocorrelogram modes (time of maximum peak) for each group. (H) Distribution of ISIs for an example RS cell (Left) and an FS cell (Center). The gray part of the distribution indicates the ISI categorized as bursts. (Right) Percentage of cells classified as bursty for each cell type. AP, action potentials. In D and G, the density probabilities were computed from kernel-smoothing density estimates of the actual data and displayed such that the sum over the whole displayed interval is equal to 100 for each group.

Fig. 3.

Putative monosynaptic connections reflect neuronal type. (A) Cross-correlogram (Lower, referenced to firing by the putative Int) implies reciprocal monosynaptic interactions between an FS Int and an RS Pyr cell identified by their autocorrelograms (y-axis display rate in Hz) and spike waveforms (Upper Left and Upper Right, respectively). The large peak in the cross-correlogram indicates that the putative Pyr cell is systematically firing ∼2 ms before the putative FS Int. Conversely, the decreased firing for 4 ms after the putative Int firing suggests that it inhibits the putative Pyr cell. Dashed green lines show the 99% confidence interval from jittered spike trains. (B) In this example a putative Pyr cell (reference of the cross-correlogram) tended to excite a putative Int at a latency of ∼3 ms. In A and B, cells were recorded on the same electrodes; because of the nature of spike detection, the central values of the cross-correlograms are thus null. (C) The sign and strength of the putative monosynaptic connections were matched to the spike's average waveform. Small dots, all neurons; large dots, identified cell that appeared to monosynaptically affect another cell. Color code for sign (blue, excitation; red, inhibition) and strength (dark, weak; light, strong) of the connection. (D) Total number of synaptic connections between pairs of cells recorded by the same first- or second-neighbor electrodes.

Fig. 4.

Spatial distribution of cell–cell interactions in an example 2D recording session. (Center Upper) Correlation values of one putative Pyr cell with all others. Color codes for the absolute value of Pearson's correlation (calculated for 50-ms bins), with black indicating low correlation and copper indicating high. (Right) Randomly chosen cross-correlograms between the reference cell and nine others sorted by correlation values. The y axis displays instantaneous rates of target cells. (Center Lower) Correlations between one putative Int and all others. (Left) Sample Int–Int cross-correlograms.

Fig. 5.

Relation of firing correlation to distance between cells. (A) Normalized coefficients of correlations were plotted against the distance between the two cells in each pair of putative Int (I–I correlations, Left) and putative Pyr (E–E correlations, Right) cells computed on time bins of 50 ms. Only the E–E group shows a significant linear regression (red and blue lines). (B) Correlation values of linear regressions for different time bins. Shaded areas indicate the 95% confidence interval (Fisher method). Numbers of cell pairs are indicated for the two populations. (C) Same as in A but normalized correlation coefficients were averaged over 0.8-mm spatial intervals. For E–E connections, the decay is well fitted with an exponential. (D) Strength and extent of spatial modulation of E–E correlations relative to the time bin width. Strength of spatial modulation is estimated with the dimensionless quantity κ/β. Green intensity codes for spatial extent of the modulation (λ). (Inset) Values (y axis) of the fitting parameters β (solid line) and κ (dotted line) in function of time bin length (x axis). (E) Same as in B but in different wake/sleep states. Analyses were restricted to cells with mean firing rate > 0.3 Hz in each particular state, resulting in the different numbers of cell pairs as indicated.