Imaging input and output of neocortical networks in vivo - PubMed (original) (raw)

Imaging input and output of neocortical networks in vivo

Jason N D Kerr et al. Proc Natl Acad Sci U S A. 2005.

Abstract

Neural activity manifests itself as complex spatiotemporal activation patterns in cell populations. Even for local neural circuits, a comprehensive description of network activity has been impossible so far. Here we demonstrate that two-photon calcium imaging of bulk-labeled tissue permits dissection of local input and output activities in rat neocortex in vivo. Besides astroglial and neuronal calcium transients, we found spontaneous calcium signals in the neuropil that were tightly correlated to the electrocorticogram. This optical encephalogram (OEG) is shown to represent bulk calcium signals in axonal structures, thus providing a measure of local input activity. Simultaneously, output activity in local neuronal populations could be derived from action potential-evoked calcium transients with single-spike resolution. By using these OEG and spike activity measures, we characterized spontaneous activity during cortical Up states. We found that (i) spiking activity is sparse (<0.1 Hz); (ii) on average, only approximately 10% of neurons are active during each Up state; (iii) this active subpopulation constantly changes with time; and (iv) spiking activity across the population is evenly distributed throughout the Up-state duration. Furthermore, the number of active neurons directly depended on the amplitude of the OEG, thus optically revealing an input-output function for the local network. We conclude that spontaneous activity in the neocortex is sparse and heterogeneously distributed in space and time across the neuronal population. The dissection of the various signal components in bulk-loaded tissue as demonstrated here will enable further studies of signal flow through cortical networks.

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Figures

Fig. 1.

Fig. 1.

Spontaneous calcium transients in cell somata and neuropil of bulk-loaded neocortical L2/3. (A)(Left) Side projection of OGB-1-loaded cells in the motor cortex. Astrocytes (yellow) were counterstained with sulforhodamine 101. (A)(Right)(Upper) Two-photon image 250 μm below pial surface showing neurons (green), astrocytes (yellow), and surrounding neuropil loaded with OGB-1. (Lower) Same area as Upper showing regions of interest: neuron (white circle), astrocyte (white square), neuropil (shaded gray), and blood vessel lumen for background (blue circle). (B) Simultaneous calcium transients from identified astrocyte (Top), neuron (Middle), and neuropil (Bottom) recorded over several minutes. (Inset) Note the sharp transients with fast onset and exponential decay (black) and ongoing neuropil signal on expanded time scale (from boxes)

Fig. 2.

Fig. 2.

Single AP-evoked calcium transients are detected in bulk-loaded tissue. (A) Overlay of OGB-1-loaded neurons (green) and astrocytes (yellow). The cell-attached recording was obtained from the center neuron (arrow indicates pipette containing 5 μM Alexa Fluor 594). (B) (Upper) Current trace from cell-attached recording showing spontaneous spikes from neuron depicted in A (number of spikes are indicated). (Lower) Simultaneously recorded somatic calcium transients corresponding to single APs as well as AP doublet. (C) Examples of somatic calcium transients (lower traces) evoked from spontaneous single APs, double APs, and triple APs from cell-attached recordings (upper traces). (D) Fidelity of spike detection confirmed with simultaneous cell-attached current recordings. The fraction of optically detected single APs and bursts of APs is shown. (E) Calcium transient amplitude as a function of the number of APs as detected from simultaneous cell-attached current recordings

Fig. 3.

Fig. 3.

Neuropil fluctuations are highly correlated with ongoing electrical activity. (A) Simultaneous measurement of membrane potential from a L2/3 pyramidal neuron using whole-cell (WC) recording, ECoG, and neuropil fluorescence fluctuation (OEG). (B) (Left) Side projection of cells superficially loaded with OGB-1 depicting depth from pia that neuropil signals were collected (dotted white lines). (Right) Ongoing OEG fluctuations (red) from different depths correlated with electrical ECoG signals (black). (C) Dendrites contribute little to OEG fluctuations. (Left) Side projection of OGB-1-loaded dendrites originating from layer 5 neurons using deep-loading technique (see Methods). (Right) Simultaneous ECoG recording (black) and OEG recording from dendrites (red). The lower traces show a recording near to the site of initial dye ejection (imaging depth indicated). (D) Peak amplitudes of neuropil calcium transients in superficially loaded cortex (▪) and deeply loaded cortex (○). (E) Plot of peak correlation of neuropil and ECoG fluctuations at different depths when OGB-1 is loaded into L2/3(▪, n = 5 animals) or discretely loaded into layer 5 (○, n = 5 animals)

Fig. 4.

Fig. 4.

Blocking postsynaptic spiking activity does not change OEG. (A) Spike-evoked calcium transients (raster plot) from 25 L2/3 neurons before, during (gray box), and after local pressure application of a specific AMPA receptor antagonist (1 mM GYKI53655). Shown are group activity during the same time periods (lower histogram; 1-s bins) and total activity of individual neurons (upper right histogram). Neuropil calcium fluctuations (red) recorded during the same period as raster plot. (B) Representative ECoG (black trace) and neuropil calcium fluctuation (red trace) periods and resulting cross correlations before and during antagonist application (taken from dotted boxes). (C) Summary of neuronal firing rates (black) and peak correlations (red) comparing preantagonist periods (pre) to antagonist periods and postantagonist periods

Fig. 5.

Fig. 5.

Distribution of activity during Up states. (A) Overlay of three spontaneous whole-cell Up states (Upper) and the simultaneous ECoG recordings (Lower) depicting variable timing of AP firing with respect to Up-state onset. Shown is the distribution of AP firing times from 43 Up states (n = 5 animals) with reference to Up-state onset (Lower). Indicated are the first (▪), second (□), and third (○) APs. APs from upper membrane potential traces are indicated by colored symbols. (B) Raster plot of somatic calcium transients in 38 neurons imaged during 20 consecutive spontaneous ECoG Up states (overlay). Each line represents peak time of the activity, and the color is associated with the color of the different Up state (overlay). (C) Histogram of activity from 220 Up states from five animals showing average (red line) time of postsynaptic activity in relation to the average Up state time course (0.1-s bins)

Fig. 6.

Fig. 6.

Heterogeneous population spiking activity. (A) Fluorescence image showing the spatial distribution of the astrocytes (yellow) and OGB-1-filled neurons (green). (B) Pseudocolored representation of imaged area in A depicting the fraction of Up states in which neurons were active during a 90-s period. Activity scale is shown; neurons that were not active within this period are colored black. (C) Raster plot depicting the percentage of neurons from one area that produce spike-evoked calcium transients during consecutive Up states. Each point represents one Up state. The average activity is depicted by the red line. (D) Population histogram for the average percentage of neurons active during many Up states from five animals. (E) Population IEI distribution pooled from many imaging periods (exponential fit, red). (F) Range of firing frequencies in which 212 neurons were active over a period of 10 min; neurons were ranked according to their average activity (red point indicates mean). (G) Probability of spiking activity in a population of neurons from five animals (same data as in E). (H) Local input-output relationship. Relative Δ_F_/F changes in OEG fluorescence (presynaptic) during an Up-state transition calculated from the preceding Down state and plotted against the absolute number of postsynaptic spiking-related events (postsynaptic) during the corresponding Up state over the entire neuronal population

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