A widespread electrical brain network encodes anxiety in health and depressive states

Abstract

In rodents, anxiety is charactered by heightened vigilance during low-threat and uncertain situations. Though activity in the frontal cortex and limbic system are fundamental to supporting this internal state, the underlying network architecture that integrates activity across brain regions to encode anxiety across animals and paradigms remains unclear. Here, we utilize parallel electrical recordings in freely behaving mice, translational paradigms known to induce anxiety, and machine learning to discover a multi-region network that encodes the anxious brain-state. The network is composed of circuits widely implicated in anxiety behavior, it generalizes across many behavioral contexts that induce anxiety, and it fails to encode multiple behavioral contexts that do not. Strikingly, the activity of this network is also principally altered in two mouse models of depression. Thus, we establish a network-level process whereby the brain encodes anxiety in health and disease.

Keywords: Anxiety; brain networks; depression; dynamics; limbic; stress.

Figure 1:. Distributed electome networks encodes anxiety states across multiple anxiety-related paradigms.

A) Local field potential oscillations recorded from 8 brain regions, concurrently, as mice were subjected to three distinct paradigms used to model anxiety. B) dCSFA-NMF results when the network model was used to discover an electome network for each anxiety paradigm. Electome networks learned for the three anxiety paradigms were applied to new mice subjected to the three paradigms (N= 13, 26, and 19 training mice for FLX, EPM and BOF, respectively, and N= 6, 11, 9 holdout mice for FLX, EPM and BOF, respectively). Nine generalization tests for each of the three learned networks were run in new mice subjected to the three different anxiety paradigms. C) Multi-assay dCSFA-NMF model used to discover a joint set of electome networks shared across the three anxiety paradigms. D) Network Consistency was evaluated by training the dCSFA-NMF model multiple times, where the mice used for training and validation were shuffled. A cosine distance metric quantified the consistency of the supervised networks across runs, where a lower cosine distance reflected greater network consistency. E) Box and whisker plots show generalization tests for which the networks learned from the multi-assay dCSFA-NMF model were applied to new mice (same as Fig. 1B) subjected to the three different anxiety paradigms. Dashed line at AUC = 0.5 corresponds to models with no predictive utility. F) Predictive utility of multi-region multi-assay dCSFA-NMF network model (same as Fig. 1E) vs. models solely based on activity from single brain regions. Models that showed significant encoding are highlighted in pink (data analyzed using a single-sample t-test against a null AUC distribution at α = 0.05, and shown as mean±s.e.m). Note that only the network model encoded all three assays.

Figure 2:. Individual electome networks within the multi-assay anxiety model independently encode distinct anxiety paradigms.

A) Power and Synchrony measures that comprise each electome network. Brain regions and frequency bands ranging from 1–56 Hz are shown around the rim of the plot. Power features are depicted as bands within the rim of the plot, and cross-spectral (i.e., synchrony) measures are depicted by the lines connecting the brain regions through the center of the circle. The top 15 percent of components for each electome network is shown. B) Granger offset measures were used to quantify directionality for the synchrony measures shown in A. Prominent directionality features were found in multiple bands coded by color. Histograms quantify the number of lead and lagging circuit interactions for each brain region. C) Schematic of directionality for each of the three electome networks. Arrows are colored to represent the dominant frequency of directionally (see color scale in panels A or B). D) Independent predictive performance of each supervised network across each anxiety assay. Mean contribution towards the joint model logistic regression predictions is also shown. Independent predictive performance of each supervised network across each anxiety assay. Tests were performed using the 17 holdout mice, and networks that showed significant encoding are highlighted in pink (data analyzed using a one-tailed unpaired t-test against a null AUC distribution at α = 0.05).

Figure 3:. Increases in Electome Network 1 and 2 activity encodes features of anxiety related paradigms.

A) Electome Network activity dynamics during fluoxetine assay. Data is plotted across 5-minute windows for Electome Network 1 (left) and 2 (right). Note that activity decreases in both networks over time following saline and fluoxetine treatment (N = 6 mice). P* <0.05 for time effect using a within and within two-way ANOVA. B) Comparison of Electome Network activity in safe zones of the EPM (closed arm) and BOF (periphery) over the duration of the assays. Time (P*), and assay (P^#) effects were determined using an analysis of covariance. Data was plotted with a 10s sliding window and shown normalized to network activity observed in the home cage. C) Mice showed avoidance of the anxiogenic zones of the EPM (left, P<0.05 using one-tailed paired t-test) and BOF (middle, P<0.05 using one-tailed paired t-test). Bout length of mice in the anxiogenic zones for EPM and BOF (right; P<0.05 using one-tailed unpaired t-test). D) Decrease in Network 1 (left) and 2 (right) activity between the first and last minute of each assay. Network 2 showed a larger activity decrease in the BOF than in the EPM (P<0.05 using one-sided Mann-Whitney U test). E-F) Average period of occupancy in safe and anxiogenic zones in E) EPM and F) BOF assays. Note that mice showed greater occupancy of the center in the second half of the BOF. G) Electome Network activity dynamics relative to arm locations in the EPM assay. Gray highlights 1 second windows when the animals are in the open or closed arms. Neural activity preceding and following these timepoints is shown as well, and data is shown normalized to the mean activity observed across the assay. The purple line highlights temporal intervals with significantly different Electome Network activity, determined using a one-tailed Wilcoxon sign rank test (N = 11 mice). H) Same as G, except data shown for the BOF assay (N=9 mice).

Figure 4:. Electome Network 1 and 2 activity does not encode arousal.

A) Mice were trained to nose poke for 5 consecutive seconds. A sucrose reward was delivered at time zero, highlighted by gray. Electome Network activity was compared prior to and following sucrose delivery using a one-tailed sign-rank test (N=9 mice). Data is shown as data is shown as mean±s.e.m. B) Electome Network activity was quantified while mice engaged with an object or a social stimulus mouse during a free interaction assay and compared using a one-tailed sign-rank test (N=12 mice). All analyses were performed in mice that were not used to learn the multi-assay anxiety model. Data is shown as data is shown as mean±s.e.m.

Figure 5:. Electome Network 1 and Network 2 activity encode distinct anxiety paradigms.

A) Mice were infected with ChR2 in ventral hippocampus (Hip) and implanted with an optrode to target lateral hypothalamus (LH). Multiwire electrodes were also implanted to target the 8 brain regions utilized to learn the multi-assay anxiety network (N=11 mice). B) Neural activity recorded during optogenetic stimulation of Hip terminals in LH with blue (473nm, 20hz, 5mW, 5ms pulses) or yellow light (593.5nm, 20hz, 5mW, 5ms pulses). Note that blue light stimulation induced activity in LH (and remotely) while yellow light stimulation did not. C) Electome Network 1 and D) Network 2 activity during yellow or blue light stimulation. Network 2 showed an increase in activity with blue vs. yellow light stimulation (P<0.001 using a one-tailed Wilcoxon sign rank test)) while Network 1 did not (P=0.14). E) Behavioral paradigm utilized to induce fear conditioning. Conditioned mice (CS+; N=10) received an air puff at the end of each tone presentation, while non-conditioned mice (CS-; N=15) did not (top). Neural activity was recorded in both groups throughout tone presentation (bottom). F) Freezing behavior in CS- and CS+ mice one to two days after exposure to the conditioning paradigm. G-H) Mean Activity of G) Electome Network 1 and H) Electome Network 2 activity within the 10 second interval prior to the presentation of the 7^th conditioning tone. I-J) Mean activity of I) Electome Network 1 and J) Electome Network 2 within the 20 second following the presentation of the 7^th conditioning tone. H-K) Mean activity of I) Network 1 and J) Network 2 in response to an air puff. Data was analyzed using a one-tailed rank sum test.

Figure 6:. Alternated Electome network activity signals behavioral disruptions in mouse models of mood disorders.

A) EPM open arm exploration in WT and ClockΔ19 mice (N=17 mice/genotype). Data was compared using a one tailed t-test. B) Neural activity was isolated when mice were in the closed arm of the EPM and Electome Network 1 (left) and 2 (right) activity was compared across genotype using an Analysis of Covariance (N=10 and 11 for WT and ClockΔ19 mice, respectively; data shown as mean±s.e.m.). C) Distinct stress paradigms utilized to model depression in mice. D) Schematic of choice interaction assay utilized to quantify susceptibility to chronic social defeat stress (left), and resultant social interaction profiles of a population of stressed mice (right). Red circles denote mice defined as susceptible (interaction ratio < 1), while green circles denote resilient mice (interaction ratio >= 1). Black circles denote non-stressed control mice. E) EPM open arm exploration in mice subjected to chronic social defeat stress (N=12 mice) and control mice (N=10 mice). Data was compared between stressed and non-stressed mice using a one-tailed t-test. Post-hoc testing between susceptible (N=5 mice) and resilient mice (N=7 mice) was performed using a two-tailed t-test. F) Electome Network 1 (left) and 2 (right) activity was quantified in the home cage and compared between chronic social defeat stressed (N=34 mice) and non-stressed controls (N=16 mice) a one-tailed rank-sum test. Post-hoc testing was compared between susceptible (N=21 mice) and resilient mice (N=13 mice) using a two-tailed rank-sum test. G) EPM open arm exploration in mice subjected to chronic mild unpredictable stress (N=11 mice) and control mice (N-11 mice). Data was compared using a one-tailed t-test. H) Electome Network 1 (left) and 2 (right) activity was quantified in the home cage and compared across groups using a one-tailed rank-sum test.

Figure 7:. Conceptual framework utilized to discover and validate electome network for anxious internal state.

A) Affective and neurophysiological states (listed on the left) induced by behavioral and experimental manipulations (listed along the top). Manipulations that were hypothesized to induce/strengthen the internal state listed to the left are highlighted by green. Manipulations that were hypothesized to decrease the internal state listed to the left are highlighted by red. Manipulations for which there is no clear prediction for the impact on the affect state listed to the left are highlighted by yellow. Mice used for each analysis are shown in the bottom row. New independent mice are highlighted in green. B) Responses of Electome Networks 1 and 2 to experimental conditions utilized throughout the study. Green and red boxes highlight conditions where network activity significantly increased or decreased, respectively. An ‘X’ is used to denote the non-significant trends observed in network activity response.