Distinct activity dynamics in VTA and LC axons during navigation of familiar environments

a, Experimental setup (top), created with BioRender.com. Example virtual reality environment. b, Schematic representation of injection procedure (left). Representative coronal brain sections immunostained for Tyrosine Hydroxolase (TH) from a DAT-Cre mouse showing overlapping expression of axon-GCaMP (green) and TH (red) in VTA neurons (top) and from a NET-Cre mouse showing overlapping expression of axon-GCaMP(green and TH (red) in LC neurons (bottom). c,. Example CA1 field of view of VTA axons (top) and LC axons (bottom). Extracted regions of interest used for example VTA and LC activity throughout the figure. d, Example DAT-Cre mouse (left) and NET-Cre mouse (right) with aligned reward delivery (top, green), mouse track position (black), ΔF /F from example roi (VTA-orange, LC-blue), and mouse velocity (bottom, gray). e, i, Position binned ΔF /F ± s.e.m in example VTA (orange) and LC (blue) ROIs during navigation of the familiar rewarded environment. ii, Population average position binned ΔF /F ± s.e.m. in VTA ROIs (orange, n = 7 ROIs in 7 mice) and LC ROIs (blue, n = 87 ROIs from 27 sessions in 17 mice) . Linear regression analysis (on all data points, not means) shows that the population of VTA ROIs increase activity during approach of the end of the track while the population of LC ROIs have consistent activity throughout all positions. Linear regression, F test, VTA, P < 1e − 21, LC, P < 0.01. iii, The LC data set was resampled 1000x using n = 7 axons to match the number of VTA Rois and the slope and intercept of the regression line were measured each time (blue dots). The VTA slope is steeper than all LC slopes indicating a stronger positive relationship between position and activity for VTA inputs. iv, Linear regression of position binned activity of individual VTA (orange diamonds), and LC (blue, circles) axons. The majority (6/7) of VTA axons show a significant positive relationship with position while LC axons show both a positive (25/87) and negative (37/87) relationship. F, i, Same example ROIs as (d) binned by velocity. ii, Same data as (d, ii,) binned by velocity. Linear regression shows that the population of VTA and LC ROIs have a significant relationship with velocity. Linear regression, F test, VTA, P < 0.05, LC,P < 1e − 68. iii, Resampling shows the VTA slope and intercept is within the resampled LC slopes and intercepts indicating similar relationships with velocity. iv, Linear regression of individual VTA and LC axons shows the majority (63/87) of LC axons have a significant positive relationship with velocity while only 2 VTA axons show this relationship. g, Same example ROIs as (d) aligned to motion onset. ii, Same data as (d, ii,) aligned to motion onset. Linear regression shows that the population of VTA axons have a negative slope prior to motion onset while LC axons have positive slope. Linear regression, F test, VTA, P < 0.01, LC, P < 1e − 65. iii, Resampling shows the VTA slope is negative while all resampled LC slopes are positive. iv, Linear regression of individual VTA and LC axons shows the majority (56/87) of LC axons have a significant positive slope prior to motion onset while the majority (4/7) of VTA axons have a negative slope.

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Removal of reward restructures VTA but not LC input activity during spatial navigation:

a. Experimental Paradigm. b.i. Population average position binned ΔF /F ± s.e.m. of VTA ROIs (n = 6 ROIs in 6 mice) in the rewarded (VTA rew, orange) and unrewarded conditions (VTA unrew, gray). Linear regression, F test, Rewarded, P < 1e − 22, Unrewarded, P < 0.001. ii. Same data as (b,i) binned by velocity. Linear regression, F test, Rewarded, P < 0.05, Unrewarded, P < 0.05. iii, Same data as (b,i) aligned to motion onset. Linear regression, F test, Rewarded, P < 1e − 4, Unrewarded, P < 0.05. c, i, Population average position binned ΔF /F ± s.e.m. of LC ROIs (n = 26 ROIs in 7 sessions in 4 mice) in the rewarded (LC rew, blue) and unrewarded conditions (LC unrew, gray). Linear regression, F test, Rewarded, P < 0.01, Unrewarded, P < 0.01. ii, Same data as (c,i) binned by velocity. Linear regression, F test, Rewarded, P < 1e − 12, Unrewarded, P < 1e − 15. iii, Same data as (c,i) aligned to motion onset. Linear regression, F test, Rewarded, P < 1e − 21, Unrewarded, P < 1e − 26. The slope of each unrewarded measure was compared to the familiar laps using a one-way ANCOVA with Tukey HSD post hoc test. * P < 0.05, ** P < 0.001, *** P < 1e − 4.

Exposure to a novel environment causes an abrupt and sustained increase in activity in LC but not VTA inputs to dCA1

a, i, Experimental Paradigm. ii, Behavior from example mouse during the transition from the familiar VR environment to a novel VR environment showing the animals track position (top, black) and velocity (bottom, gray). iii, The average running velocity ± s.e.m. of all mice during the transition to a novel VR environment (top). The average freezing ratio of all mice ± s.e.m., calculated as the time spent immobile (velocity < 5cm/s) divided by the total lap time. Each lap was compared to the first lap in F using a one-way ANOVA with Tukey HSD post hoc test. * P < 0.05 b, Mean normalized F of all VTA ROIs (top, n = 7) and LC ROIs (bottom, n = 87) aligned to the switch to the novel environment. To define a baseline and 95% CI (gray shaded region), 1000 shuffles were created from the calcium traces and down sampled to match the sample size and averaged. This was repeated 1000 times and the mean and 95% CI of this shuffled data was determined for each frame. Red lines indicate periods where two or more consecutive frames passed above the % CI of the shuffled baseline. c, Normalized ΔF /F activity of all VTA ROIs (top) and LC ROIs (bottom) aligned to the switch to the novel VR environment. d, The normalized fluorescence of all LC ROIs binned by lap (left) or into 50 frame bins (right). The baseline and 95% CI (gray shaded region) was defined using the same method as in (b) Red lines indicate bins above the baseline 95% CI.

Novelty-induced changes in behavior explain the late but not early increases in LC activity

a, Good behavior from example mouse following removal of freezing periods (velocity < 0.2 cm/s) during the transition from the familiar to a novel VR environment showing the animals track position (top, black) and velocity (bottom, gray). b, Normalized ΔF /F activity of all LC ROIs aligned to the switch to the novel VR environment following removal of freezing periods. c, Mean normalized F of all VTA ROIs (top, n = 7) and LC ROIs (bottom, n = 90) aligned to the switch to the novel environment. To define a baseline and 95% CI (gray shaded region), 1000 shuffles were created from the calcium traces and down sampled to match the sample size and averaged. This was repeated 1000 times and the mean and 95% CI of this shuffled data was determined for each frame. Red lines indicate periods where two or more consecutive frames passed above the 95% CI of the shuffled baseline. d,e,. The normalized F of all LC ROIs binned by lap (d) or into 50 frame bins (e). The baseline and 95% CI (gray shaded region) was defined using the same method as in (c). Red lines indicate bins above the baseline 95% CI. f-h, Population average position binned (f), velocity binned (g), and motion onset aligned (h) ΔF /F ± s.e.m. in LC ROIs (n = 90) in the final laps of the familiar environment (light blue), and the first (orange), third (dark blue), and final laps (green) of the novel environment. Linear regression, F test, position binned (f) fam last, P < 1e − 4, nov 1, P < 1e − 68, nov 3, P = 0.48, nov last, P < 0.001; velocity binned (g) fam last, P < 1e − 31, nov 1, P < 0.05, nov 3, P < 1e − 5, nov last, P < 1e − 13; motion onset aligned (h) fam last, P < 1e − 29, nov 1, P < 0.001, nov 3, P < 1e − 9, nov last, P < 1e − 18. The slope of each lap was compared to the final familiar laps using a one-way ANCOVA with Tukey HSD post hoc test. * P < 0.01, ** P < 0.001, *** P < 1e − 4.

a,i, Population average position binned ΔF /F ± s.e.m. of VTA ROIs (n = 7 ROIs in 7 mice) in the familiar (orange) and novel (green) rewarded environments. Linear regression, F test, Rewarded, P < 1e − 21, Unrewarded, P < 0.01. ii, Same data as (a,i) binned by velocity. Linear regression, F test, Rewarded, P < 0.05, Unrewarded, P = 0.57. iii, Same data as (a,i) aligned to motion onset. Linear regression, F test, Rewarded, P < 0.01, Unrewarded, P < 0.001. The slope of each novel measure was compared to the familiar laps using a one-way ANCOVA with Tukey HSD post hoc test. * P < 0.05, ** P < 0.001, *** P < 1e − 4.