Selective Modulation of Orbitofrontal Network Activity during Negative Occasion Setting

Abstract

Discrete cues can gain powerful control over behavior to help an animal anticipate and cope with upcoming events. This is important in conditions where understanding the relationship between complex stimuli provides a means to resolving situational ambiguity. However, it is unclear how cortical circuits generate and maintain these signals that conditionally regulate behavior. To address this, we established a Pavlovian serial feature-negative conditioning paradigm, where male mice are trained on a trial in which a conditioned stimulus (CS) is presented alone and followed by reward, or a feature-negative trial in which the CS is preceded by a feature cue indicating there is no reward. Mice learn to respond with anticipatory licking to a solitary CS, but significantly suppress their responding to the same cue during feature-negative trials. We show that the feature cue forms a selective association with its paired CS, because the ability of the feature to transfer its suppressive properties to a separately rewarded cue is limited. Next, to examine the underlying neural dynamics, we conduct recordings in the orbitofrontal cortex (OFC). We find that the feature cue significantly and selectively inhibits CS-evoked activity. Finally, we find that the feature triggers a distinct OFC network state during the delay period between the feature and CS, establishing a potential link between the feature and future events. Together, our findings suggest that OFC dynamics are modulated by the feature cue and its associated conditioned stimulus in a manner consistent with an occasion setting model.SIGNIFICANCE STATEMENT The ability of patterned cues to form an inhibitory relationship with ambiguously rewarded outcomes has been appreciated since early studies on learning and memory. However, it was often assumed that these cues, despite their hierarchical nature, still made direct associative links with neural rewarding events. This model was significantly challenged, largely by the work of Holland and colleagues, who demonstrated that under certain conditions cues can inherit occasion setting properties whereby they modulate the ability of a paired cue to elicit its conditioned response. Here we provide some of the first evidence that the activity of a cortical circuit is selectively modulated by such cues, thereby providing insight into the mechanisms of higher order learning.

Keywords: negative occasion setting; orbitofrontal cortex; single-unit electrophysiology.

Figure 1.

Distinct associations form from feature-negative conditioning. A, Schematic of the four distinct trial types used during training and recording sessions. In rewarded trials (CS1⁺ and CS2⁺), different conditioned odor stimuli (CS1 or CS2, 1 s duration) predicted the delivery of reward. In unrewarded trials (CS1⁻), when the same odor stimuli were preceded by a feature cue (mild air puff, 0.5 s duration), there was no reward. Orange bar, Feature; gray bar, CS1; green bar, CS2; black bar, reward. B, Probability of presenting each trial type during initial training (left) and on the final training session corresponding to recording (right). All behavioral and electrophysiological results are from the final day. C, D, Average lick rate as a function of time during all rewarded and unrewarded trials. Dashed lines represent the onset and offset times of the indicated cue. Data represent mean ± SEM (n = 8 mice). E, The feature significantly reduces the likelihood that animals express anticipatory licking (t = 0–2.5 from odor onset) in CS1 trials (p < 0.0001, paired t test). F, The feature significantly suppresses the likelihood of anticipatory licking in transfer trials (p = 0.03, paired t test).

Figure 2.

Silicon microprobe recordings in the OFC. A, Representative confocal image of a coronal section showing the recording position of the silicon microprobe containing four prongs. Before insertion, the prongs were painted with DiD (red) to facilitate visualization. The section was stained with DAPI (blue). B, Coronal section from the Franklin and Paxinos (1997) mouse brain atlas (2.35 mm anterior to bregma) annotated with the estimated position of each putative unit (red dot) in relation to the OFC structure.

Figure 3.

Cue-dependent modulation of OFC activity. A–C, Mean firing rate as a function of time in different trial types. Dashed lines represent the onset and offset times of the indicated cue. Data represent mean ± SEM (n = 585 units). Gray bar, CS1; green bar, CS2; orange bar, feature. A, Comparison of CS1⁺ with CS1⁻ trials. B, Comparison of CS2⁺ with transfer trials. C, Comparison of CS1⁻ trials with licking or without anticipatory licking. D–F, Mean firing rate per animal during the CS presentation period (t = 0–1 s), in different trial conditions. Data represent individual animals (n = 8). D, CS1⁻ trials exhibit significantly lower firing than CS1⁺ trials (p = 0.016, paired t test). E, There is no significant difference in mean firing between transfer trials and CS2⁺ trials (p = 0.46, paired t test). F, There is no significant difference in mean firing between CS1⁻ trials with licking and those without licking (p = 0.3, paired t test). G, Comparison of the average firing rate per unit during the CS cue presentation period (t = 0–1 s) between CS1⁺ and CS1⁻ trial types. Across the population (n = 585) there was a significant bias toward lower firing during CS1⁻ trials (p < 0.0001, paired t test). H, Behavioral discrimination (percentage correct CS1⁺ trials minus percentage incorrect CS1⁻ trials) is significantly correlated with the percentage of OFC units per animal that discriminate between CS1⁺ and CS1⁻ trials (Pearson r = 0.82, p = 0.012).

Figure 4.

Identification of temporally distinct feature encoding populations. A, Mean normalized firing rate as a function of time of the recorded population (n = 585 cells). Each cell's firing rate is normalized to its peak firing rate on CS⁻ trials (top) and CS⁺ trials (bottom). Units are ordered by latency to peak firing relative to onset of the feature cue (FT). Units are plotted in the same order in the top and bottom panels (red indicates high firing rate). B, Venn diagram showing the overlapping relationship between units that were significantly modulated by the feature cue (orange), the CS1 cue during CS1⁺ trials (magenta), and the CS1 cue during CS1⁻ trials (blue). Values represent the median percentage of modulated cells across n = 8 animals. C, Distribution of the latency to peak firing for the recorded population (n = 585 units). Two major peaks were resolved using Lorentzian curve fits (red line). Dashed orange lines demarcate the onset and offset cell populations. D, Mean firing rate as a function of time during CS1⁺ and CS1⁻ trials. The top and bottom panels are comprised of onset and offset cells, respectively. Data represent mean ± SEM (n = 585 units). The orange shaded area represents the time during the feature cue presentation. E, The percentage of cells that discriminated between CS1⁺ and CS1⁻ trials was significantly higher in the onset cell population (n = 8 mice, p < 0.0001, paired t test).

Figure 5.

A distinct network state initiated by the feature cue. A, There is no significant difference in mean OFC firing rate during the final 1 s of the DL period and a 1 s BL period before feature cue presentation (p = 0.11, paired t test). B, Strategy used to determine whether the network state in the BL period is distinct from that of the DL period. This two-step process required training (top dashed box) and testing (bottom dashed box) a binary classifier. During testing, each period (BL, green arrows; DL, blue arrows) was classified as either a correct match (e.g., BL classified as BL, solid arrow) or an incorrect match (e.g., BL classified as DL, dashed arrow). C, Mean classifier accuracy per animal of the classifier in B (accuracy defined as the percentage of correctly classified BL and DL periods across all tested folds, black) was significantly above chance levels shown in red (n = 8, p < 0.0001, paired t test). The average accuracy across the experimental group was 69 ± 2% (mean ± SEM, dashed black line). D, Strategy used to classify whether delay period activity before incorrect CS1⁻ trials (DLL), was more similar to the baseline period before correct CS1⁺ trials (BLL), or the delay period before correct CS1⁻ trials (DLW). The classifier was trained (top dashed box) to distinguish population activity during BLL periods from DLW periods. During testing (bottom dashed box) DLL activity was compared with BLL and DLW activity and classified as more similar to either BLL (dashed line) or DLW (solid line). E, Mean classifier accuracy per animal of the classifier in D (accuracy defined as the percentage of DLL periods that were labeled as DLW, black) was significantly above chance levels shown in red (n = 7, p = 0.018, paired t test). The average accuracy across the experimental group was 64 ± 4% (mean ± SEM, dashed black line). Note that animal 1 only had one DLL trial and was excluded from the analysis in E. Error bars in C and E represent 95% confidence intervals across all iterations and dashed lines represent the average values across all animals.