Paraventricular Thalamus Projection Neurons Integrate Cortical and Hypothalamic Signals for Cue-Reward Processing

Abstract

The paraventricular thalamus (PVT) is an interface for brain reward circuits, with input signals arising from structures, such as prefrontal cortex and hypothalamus, that are broadcast to downstream limbic targets. However, the precise synaptic connectivity, activity, and function of PVT circuitry for reward processing are unclear. Here, using in vivo two-photon calcium imaging, we find that PVT neurons projecting to the nucleus accumbens (PVT-NAc) develop inhibitory responses to reward-predictive cues coding for both cue-reward associative information and behavior. The multiplexed activity in PVT-NAc neurons is directed by opposing activity patterns in prefrontal and lateral hypothalamic afferent axons. Further, we find that prefrontal cue encoding may maintain accurate cue-reward processing, as optogenetic disruption of this encoding induced long-lasting effects on downstream PVT-NAc cue responses and behavioral cue discrimination. Together, these data reveal that PVT-NAc neurons act as an interface for reward processing by integrating relevant inputs to accurately inform reward-seeking behavior.

Keywords: behavioral optogenetics; drug addiction; feeding; lateral hypothalamus; learning; memory; midline thalamus; multiphoton calcium imaging; prelimbic cortex; sucrose seeking.

Figure 1.. PVT-NAc neurons develop an inhibitory, multiplexed response to reward-predictive cues across learning.

(A–B) Schematics showing head fixation for two-photon imaging experiments (A) and design of Pavlovian conditioning procedures (B; TI, trace interval). (C) Example data showing averaged licking frequency during the CS+ and CS− for a single mouse early (left) and late (right) in learning. (D) Grouped data showing lick rates during the CS+ versus CS− (left). Higher cue discrimination scores (right) during sessions late in learning (n=7 mice, 12 sessions) versus sessions early in learning (n=6 mice, 9 sessions; t₁₉=16.7, p<0.001). Data are mean ± standard error. (E-F) Viral strategy (E) allowed recordings of GCaMP6s-expressing PVT-NAc neurons (early, 9 FOVs, n=312 neurons; late, 12 FOVs, n=417 neurons) in vivo (F). (G-H) Fluorescent traces from a tracked example neuron (G) and heat plots from all neurons (H) showing cue responses in sessions early and late in learning. (I) Representative images showing PVT-NAc cells tracked across learning. (J) Neuronal cue responses from cells tracked across learning (n=5 mice, 7 FOVs, 124 neurons). (K) Quantification of tracked responses showing the proportion of cells that showed increased activity (purple), no change (white) or reduced activity (green) in response to the CS− or CS+ during a session late in learning versus a session early in learning (corrected auROC p-value<0.05 for significant ‘changers’). More cells developed reduced activity (versus cells showing increased activity) during the CS+ across learning (χ²⁼17.7, p<0.001). An equivalent number of cells developed reduced activity (versus cells showing increased activity) during the CS− across learning (χ²=2.1, p=0.15). (L) Tracked cue responses in CS+ changers only (n=52 reducers; 14 increasers), revealing that CS+ but not CS− responses were displayed late in learning, whereas no differences were displayed early in learning (CS+, 2-way ANOVA: Interaction F_1,64=152.0, p<0.001; CS-, 2-way ANOVA: F_1,64=2.3, p=0.14; *** indicates post-hoc p<0.001). Data are mean ± standard error. (M) Cumulative distribution frequency (CDF) plots showing the dynamics of individual PVT-NAc neurons could be used to predict the timing of the CS+ late in learning (left, versus early in learning: Welch’s t_711.8=13.8, p<0.001) and could also be used to predict licking frequency (right, versus shuffled: Welch’s t_809.1=6.5, p<0.001). EarlySh, shuffled data from sessions early in learning; LateSh, shuffled data from sessions late in learning. See also Figures S1, S2, and S3.

Figure 2.. PFC glutamatergic and LHA GABAergic neurons provide synaptic input to PVT NAc neurons.

(A–B) Labeling of PVT-NAc neurons (A) and PFC axons resulted in co-localization of PVT–NAc^eYFP+ neurons and PFC^tdT+ axons (B). Scale bars are 500μm (A, main image), 250μm (B, main image), and 25μm (insets). (C) Representative EPSCs evoked by optogenetic stimulation of PFC axons during patch-clamp recordings (n=4 mice, 24 neurons). (D) Grouped data showing that 79% of recorded PVT-NAc neurons displayed EPSCs in response to optogenetic stimulation of PFC axons, whereas 0% showed IPSCs. (E) Labeling of PVT-NAc neurons and LHA axons resulted in co-localization of PVT-NAc^eYFP+ neurons and LHA^tdT+ axons. Scale bars are 250μm (main image) and 25μm (inset). (F) Representative IPSCs evoked by optogenetic stimulation of LHA axons during patch-clamp recordings (n=2 mice, 26 neurons). (G) Grouped data showing that 100% of recorded PVT-NAc neurons displayed IPSCs in response to optogenetic stimulation of LHA axons, whereas only 35% showed EPSCs. See also Figure S3.

Figure 3.. PFC and LHA axons that innervate the PVT display distinct response dynamics.

(A-B) Viral strategy (A) allowed recordings of GCaMP6s-expressing PFC axons (see arrows; early learning, n=4 mice, 4 FOVs, 36 axons; late learning, n=4 mice, 4 FOVs, 37 axons) in vivo (B). (C-D) Population heat plots showing averaged CS− responses (C) and CS+ responses (D) for each PFC axon in sessions early in learning (top) and late in learning (middle). Fluorescent traces show cue responses averaged across all neurons (bottom). (E) Cumulative distribution frequency (CDF) plots showing that the dynamics of individual PFC axons could be used to more accurately predict the timing of the CS+ late in learning versus early in learning (top, Welch’s t_67.4=3.8, p<0.001), but could not be used to accurately predict licking frequency (bottom, versus shuffled: Welch’s t_71.6=0.9, p=0.35). EarlySh, shuffled data from sessions early in learning; LateSh, shuffled data from sessions late in learning. (F-G) Viral strategy (F) allowed recordings of GCaMP6s-expressing LHA axons (see arrows; early, n=4 mice, 4 FOVs, 34 axons; late, n=4 mice, 4 FOVs, n=31 axons) in vivo (G). (H-I) Population heat plots showing averaged CS-responses (H) and CS+ responses (I) for each LHA axon in sessions early in learning (top) and late in learning (middle). Fluorescent traces show cue responses averaged across all neurons (bottom). (J) Cumulative distribution frequency (CDF) plots showing that the dynamics of individual LHA axons could not be used to accurately predict the timing of the CS+ late in learning (top, versus CS+ predictions early in learning: Welch’s t_61.2=0.92, p=0.36), but could be used to accurately predict licking frequency (bottom, versus shuffled: Welch’s t_59.2=2.5, p=0.01). EarlySh, shuffled data from sessions early in learning; LateSh, shuffled data from sessions late in learning. See also Figure S3.

Figure 4.. PFC axon stimulation persistently impairs PVT-NAc cue encoding and behavioral cue discrimination.

(A) Viral strategy for optogenetic excitation of PFC axons during two-photon calcium imaging of PVT-NAc neurons. (B) Cell map, activation overlay (top; red pixels are those with increased fluorescence during activation of PFC axons), and representative traces (bottom) showing optogenetic activation of PFC axons reliably induced excitatory fluorescent deflections in PVT-NAc neurons (n=3 mice, 5 FOVs). (C) Population heat plot from all PVT-NAc neurons showing averaged CS+ responses during the Pre-Opto session (n=197 neurons), Opto session (n=165 neurons), and Post-Opto session (n=184 neurons). (D) Fluorescence traces showing CS+ and CS− responses averaged across all PVT-NAc neurons. (E) Neuronal CS+ and CS− responses from all cells tracked from the Pre-Opto session to Post-Opto session (n=95 neurons). (F) Tracked cue responses in Pre-Opto CS+ responding neurons (n=36 inhibited, 15 excited). Data show CS+ responses were attenuated during the Post-Opto session in inhibited neurons (t₃₅=−4.7, p<0.001) and in excited neurons (t₁₄=4.2, p<0.001), whereas CS− responses were unchanged (inhibited neurons, t₃₅=0.3, p=0.7; excited neurons, t₁₄=0.5, p=0.7). Data are mean ± standard error. (G) Cumulative distribution frequency (CDF) plots showing that the activity of PVT-NAc neurons more accurately predicted CS+ timing during the Pre-Opto versus Post-Opto session (left, Welch’s t_376.6=3.2, p=0.001). Activity more accurately predicted licking frequency during the Post-Opto session (right, Welch’s t_254.9=3.0, p=0.003). PreSh, shuffled data from sessions before optogenetic stimulation; PostSh, shuffled data from sessions after optogenetic stimulation. (H) Grouped behavioral data revealing equivalent lick probability during the CS− for all sessions (left, ANOVA: F_2,8=1.0, p=0.4; n=5). Lick probability was less during the CS+ for the Opto and Post-Opto sessions, versus the Pre-Opto session (middle, ANOVA: F_2,8=14.5, p=0.002; n=5). Cue discrimination scores were lower during the Opto and Post-Opto sessions, as compared to the Pre-Opto session (right, ANOVA: F_2,8=11.2, p=0.005; n=5; **indicates Newman Keuls post-hoc p<0.01). Data are mean ± standard error. (I) Grouped behavioral data revealing that in trials wherein mice licked during the CS+, the lick bout frequency was equivalent across sessions (ANOVA: F_2,8=1.6, p=0.3; n=5). Data are mean ± standard error. See also Figure S3 and S4.