Fast updating feedback from piriform cortex to the olfactory bulb relays multimodal reward contingency signals during rule-reversal

Abstract

While animals readily adjust their behavior to adapt to relevant changes in the environment, the neural pathways enabling these changes remain largely unknown. Here, using multiphoton imaging, we investigated whether feedback from the piriform cortex to the olfactory bulb supports such behavioral flexibility. To this end, we engaged head-fixed mice in a multimodal rule-reversal task guided by olfactory and auditory cues. Both odor and, surprisingly, the sound cues triggered cortical bulbar feedback responses which preceded the behavioral report. Responses to the same sensory cue were strongly modulated upon changes in stimulus-reward contingency (rule reversals). The re-shaping of individual bouton responses occurred within seconds of the rule-reversal events and was correlated with changes in the behavior. Optogenetic perturbation of cortical feedback within the bulb disrupted the behavioral performance. Our results indicate that the piriform-to-olfactory bulb feedback carries reward contingency signals and is rapidly re-formatted according to changes in the behavioral context.

Keywords: PCA; cortical bulbar feedback; multilayer perceptrons; optogenetic manipulations; piriform cortex; rule-reversal; two photon calcium imaging.

Figure 1.. A Go/No-Go rule-reversal task using olfactory and auditory cues.

(a) Schematics of a behavior session and example field of view. (Left) An olfactory (1% ethyl valerate) or auditory (6.2 KHz tone) cue was delivered randomly in each trial, and each session was divided into stimulus-reward contingency blocks of ~45 trials. Stimulus-reward contingency was alternated between ‘Sound Go blocks’ (containing Sound Go and Odor No-Go trials) and ‘Odor Go blocks’ (containing Odor Go and Sound No-Go trials). (Right) Mice virally expressing GCaMP5 in the anterior piriform cortex (aPCx) with a chronic cranial window implanted above the olfactory bulb (Methods, scale bar: 500 μm). (Inset) Example field of view (FOV) of cortical bulbar feedback boutons in the granule cell layer (~300 μm from the bulb surface, scale bar: 30 μm). (b) In the ‘delay’ task, a variable baseline period of (~9 ± ≤0.3 s) was followed by the delivery of a brief odor or sound cue (0.35 s) and a fixed 0.5 s interval (delay period) before the time when the reward became available. Mice were trained to report their decision (lick vs. no-lick) within a 1.5 s window from the end of the delay period. (c) Example in-session behavioral performance comparisons between early training (Top) and expert (Bottom) sessions. Performance was quantified using a moving average window (bin size = 10 trials, Methods). (d) Progression in the behavioral performance across sessions in the delay version of the task (n = 9 mice). (Top) Average behavior session performance. Zero marks the first session when mice experienced rule-reversal in the stimulus-reward contingency. (Bottom) Average number of trials to reach 70% performance after each rule-reversal event (Methods). (e) (Top) Example licks (dots) from odor and sound trials (Top vs. Bottom rows) parsed by trial instruction (Go: Left; No-Go trials: Right) from one delay session. (Bottom) Distributions of latency to the first-lick from cue onset from all delay sessions parsed by cue (blue: odor; yellow: sound trials). All panels error bars: ±SEM.

Figure 2:. Fast update of cortical bulbar feedback representations following reward-rule switching in task-engaged mice.

(a) Example average responses of 4 cortical bulbar boutons to odor and sound cues during Go (blue) and No-Go (red) trials. Shaded areas mark different task periods: cue (gray); delay (green); report (pink). Blue/red traces represent the average change in fluorescence (z scored) across trials; shaded area corresponds to SEM. Note the different response amplitude scales. (b,c) Example boutons that displayed stable (Left) or unstable (Right) average responses to odor (b) and sound (c) across conditions (Go vs. No-Go) assessed throughout the cue and delay periods. (d) Bouton responses (z-scored) averaged throughout the delay period and shown across trials in an example field of view from an expert mouse performing the rule-reversal task. Each row shows the response of one bouton across and blocks (Odor Go; Sound Go, Odor Go, etc.) throughout the behavior session. Boutons are sorted from top to bottom by the strength of their response during the odor trials. Color scale bar: Average z-score. Color-coded bars on top mark the block structure (Odor Go block vs. Sound Go block), cue identity (Odor vs. Sound) and trial outcome (Correct vs. Incorrect). (e) (Top). Same session as (d) re-sorted by cue identity: odor trials (Left) and sound trials (Right). Boutons were classified as enhanced, unresponsive, suppressed or complex (enhanced + suppressed) as per their response strength and polarity to the odor cue; (Right) same ordering of boutons was kept for the sound trials. (Bottom) Inter-block correlation analysis (Odor Go vs. Sound Go blocks): Pearson correlation coefficient calculated between the average feedback bouton ensemble response vector in the first Sound Go (purple) or first Odor Go (orange) block in the session and the ensemble bouton response vector of each trial; panels are sorted by the cue identity (Odor – Left; Sound - Right). (f) Average z-scored response values during the delay period parsed by cue (Odor or Sound) and instruction (Go or No-Go) for the responsive boutons sampled. Each pair of connected colored dots represents average z-scored response values computed across conditions (Go vs. No-Go) using the boutons from one behavior session. Black dots represent average z-scored ensemble bouton response across sessions. (g) Average inter-block correlation coefficients obtained as described in d for all fields of view (delay version); the first ‘Odor-Go block’ (Left) or ‘Sound-Go block’ (Right) in a session was used as reference for calculating the average feedback bouton ensemble response vector for odor and sound trials. Student’s t-test: *** = p < 0.0001. Each pair of gray connected dots represents the inter-block correlation values computed for one behavior session. Black dots represent the average correlation. (h) Same analysis as in (g) including comparisons across modalities (e.g. Odor Go trials to Sound Go trials, etc.). All panels error bars: ± SEM.

Figure 3.. Cortical bulbar feedback represents stimulus identity, contingency, and behavioral outcome.

(a) Histogram of individual bouton response correlation values across trials as a function of trial behavioral contingency (Hits, H vs. false alarms, FA vs. correct rejections, CR) in Odor (Left) and Sound (Right) trials. Bouton responses were sampled between cue onset and the end of delay period (before licking, Methods). Shaded areas correspond to SEM; Inset: Bouton response stability across conditions (H/H, H/CR, H/FA, CR/FA) reported using as reference the 90^th percentile of the Hit/Hit bouton response correlation distribution (bootstrap analysis, Methods). (b) Individual bouton response stability analysis for trials where mice subsequently licked the reward spout (hits and false alarms). Note the differences in trial-to-trial response correlation distributions when comparing Odor H/H vs. Odor H/FA vs. Odor FA/Sound FA trials. (c) Principal component analysis (PCA) for one example session: cortical bulbar feedback bouton ensemble response trajectories plotted in a space defined by the first three principal components (74.5 and 73.7 % variance explained respectively for odor and sound trials); population response trajectories rapidly diverge as a function of trial contingency (hits - blue vs. correct rejections - red vs. false alarms - green) for both Odor (Left) and Sound (Right) trials. Miss (M) trials were excluded from the analysis due to their low frequency (< 3%). Different task periods in each trajectory are represented by distinct traces (baseline: thin continuous; cue: thick continuous; delay: thick interrupted; report: thick dotted line). (d) Multi-layer perceptron classifiers were trained to decode stimulus identity (odor or sound), behavioral contingency (H, FA, CR), trial instruction (Go or No-Go), and behavior (lick or no-lick) in the delay version of the task. Top: Average classifier performance across all sessions normalized relative to baseline performance. When shuffling trial labels on the training data, the average classifier performance was 0. Bottom: Distribution of the number of licks per second across all sessions. (e) Example average responses of individual cortical bulbar bouton responses to Go (Sound A, Left) and No-Go (Sound B, Right) cues in a sound vs. sound Go/No-Go task. Shaded areas mark different task periods: cue (gray); delay (green); report (pink). Blue/red traces represent the average change in fluorescence across trials (z-scored); shaded area corresponds to SEM. (f) Average cortical feedback bouton responses in example fields of view parsed by instruction (Go or No-Go) and across days of training (naïve, day 4, and day 6). (g) Average multi-layer perceptron performance for decoding the instruction signals (Go vs. No Go) across training sessions (N=20 FOVs, 3 mice) for the task in e,f. (h) Peak performance of the classifier sampled from cue onset to the end of the delay period in the two sounds Go/No-Go task. All panels error bars: ±SEM.

Figure 4.. Cortical bulbar feedback activity mirrors the perceived reward-rule:

(a) Example bouton responses during block transitions sampled throughout the ‘delay-period’ (from cue offset and before behavioral reporting) from one field of view in an expert mouse. (Top) Odor trials. (Bottom) Sound trials. Each panel shows two block transitions (columns) across 40 responsive boutons in the field of view. Gray bars mark the trial outcome (correct – light gray; incorrect-dark gray). Asterisks mark the example bouton responses shown in (b). (b) Example individual bouton response time traces from (a) to odor (Top) and sound (Bottom) before (negative trial index) and after (positive trial index) the contingency switch (0; vertical segmented line). Interpolated responses are shown (Methods). (c) Block transition neuronal distance analysis: Pearson correlation (ρ) was calculated between the cortical feedback bouton ensemble response of a given trial of the current block and the average bouton ensemble response over the last five trials of the preceding block. The neuronal distance is defined as 1 – ρ, and shown for the first twelve trials of a given block as an average across blocks and sessions. (d) Average behavioral performance following block transitions across sessions quantified using a three-frames sliding window. (e) Correlation between the neuronal distance and the block behavioral performance showed in c and d. Color bar: Trial index of each correlation value. (f) Optogenetic perturbation of aPCx-originating feedback performed locally within the olfactory bulb; mice bilaterally expressing Jaws in aPCx neurons were chronically implanted with optic fiber cannulas placed on top of each bulb hemisphere and trained in the rule-reversal task. In expert mice, cortical feedback was suppressed (2.4 mW, 595nm) in 25% of the trials of a behavior session. (g) Behavioral performance quantified for odor (Left) and sound (Right) trials independently in Jaws-aPCx and EGFP-aPCx expressing mice respectively: (Jaws – no-light) vs. (Jaws – 2.4 mW) light-on trials. ANOVA and ‘Multiple comparisons of means’: *** = p < 0.0001; n.s.: non-significant. All panels error bars: ±SEM.