Model-based reasoning requires using information about the structure of the world to infer information on-the-fly. This ability relies on a circuit involving the orbitofrontal cortex (OFC), as evidenced by the finding that humans and laboratory animals cannot infer value in several situations when OFC function is impaired (Gallagher et al., 1999; Izquierdo et al., 2004; McDannald et al., 2005; Takahashi et al., 2009; West et al., 2011; Gremel and Costa, 2013; Reber et al., 2017; Howard et al., 2020). Model-based reasoning can be isolated in sensory preconditioning (Brogden, 1939). During this task, subjects first learn an association between neutral or valueless stimuli. If one of these stimuli is thereafter paired with a biologically meaningful stimulus (e.g. food), presentation of the never-reward-paired preconditioned stimulus will produce a strong food-approach response. This demonstrates that subjects formed an associative model in which the preconditioned cue predicts the conditioned cue, which can subsequently be mobilized to produce a food-approach response when the preconditioned cue is presented. Because the preconditioned cue itself was never reinforced, this response to the preconditioned cue cannot be explained by model-free mechanisms. Preconditioned responding is reflective of the ability of subjects to infer value on-the-fly using knowledge about the associative structure of the information acquired during preconditioning.

Previous work from our lab has shown that the lateral OFC activity is necessary for inferring the value of never-reinforced sensory stimuli in the probe test at the end of sensory preconditioning (Jones et al., 2012). Interestingly, subsequent single-unit recording showed that neural activity in the OFC reflects not only the value predictions in the final probe test, but also tracks acquisition of the sensory-sensory associations in the initial phase of training (Sadacca et al., 2018). This result suggested a wider role for OFC in building associative models, independent of encoding of overt biological significance or value, the role often ascribed to this region (Kringelbach, 2005; Padoa-Schioppa and Assad, 2006; Padoa-Schioppa, 2011; Levy and Glimcher, 2012).

Of course, single-unit recording is correlative and cannot demonstrate that OFC activity is necessary for proper acquisition of the sensory-sensory associations during preconditioning. The correlates could simply reflect activity in primary sensory (Engineer et al., 2008; Garrido et al., 2009; Headley and Weinberger, 2015) or other cortical areas that are necessary in the first phase (Port et al., 1987; Robinson et al., 2011; Robinson et al., 2014; Fournier et al., 2020). If this is the case, then interference with processing in OFC during preconditioning should not affect responding to the preconditioned cue during the probe test. On the other hand, if the representations of the sensory-sensory associations formed in OFC in the initial phase contribute to building the model of the task used to infer value and drive responding in the probe test, then interference with processing in OFC during preconditioning should affect probe test responding, either directly impairing normal responding to the preconditioned cue, if responding in our task is entirely model-based as we have suggested (Jones et al., 2012; Sadacca et al., 2018), or by making any responding insensitive to devaluation of the predicted food reward, if responding in the probe is partly maintained by transfer of cached value to the cue during conditioning (Doll and Daw, 2016). Here we tested for such functional effects by training rats on a sensory preconditioning task nearly identical to those previously used by our lab (Jones et al., 2012; Sharpe et al., 2017; Sadacca et al., 2018), optogenetically inactivating the lateral OFC during cue presentation in the preconditioning phase of training and adding an additional assessment of responding after devaluation at the end of the experiment. We found that interfering with processing in OFC during the preconditioning phase completely abolished responding to the preconditioned cue in the probe test after conditioning, responding that in controls was subsequently disrupted by devaluation of the expected food reward.

While the OFC is generally thought to contribute to behavior where there are changes in, or computations of, value (Gallagher et al., 1999; Kringelbach, 2005; Padoa-Schioppa and Assad, 2006; Schoenbaum et al., 2011), our lab recently showed that neural activity in lateral OFC can also track the development of valueless sensory-sensory associative information in a sensory preconditioning task (Sadacca et al., 2018). While performance in the final phase of this task is ultimately sensitive to OFC manipulations in both rats (Jones et al., 2012) and humans (Wang et al., 2020b), the development of neural correlates of neutral sensory associations in the initial phase of training suggested that OFC might not be restricted to encoding information once clear biological significance is established and instead could be more widely involved in representing structure among features of the environment, with value being just one of these features. Here we tested this question by optogenetically-inactivating the OFC during the initial phase of preconditioning, when correlates were previously observed, and we found that this manipulation also disrupted performance in the final phase of the task. These findings are consistent with the argument that the associative correlates we observed during preconditioning in our prior study are not simply downstream reflections of sensory or other cortical processing and instead must contribute to the construction of the model used to guide responding in the final probe test. These data are also in accord with the findings that OFC represents not only value, but also features of the environment such as trial type (Lopatina et al., 2017), sequence (Zhou et al., 2019), direction, and goal location (Feierstein et al., 2006; Mainen and Kepecs, 2009).

These results come with several important considerations that are worth discussing. The first is whether OFC inhibition caused the rats to simply generalize between the preconditioned cues. In considering this possibility, we would first note that generalization or failure to treat these cues differently would be to some extent the final common outcome of disrupting the more detailed encoding of their identities and different associative relationships to reward that we argue is affected. For that reason, it is difficult to formally rule this out. However we believe that generalization as a primary cause is unlikely given the low overall levels of responding to these cues during the probe, relative to responses to the reward-paired cue. Additionally, responding to the two preconditioned cues in the experimental group was no different than responding to the preconditioned cue predicting reward in the control group. If generalization alone accounted for the results, we would expect higher levels of responding to both cues during the probe in the OFC-inhibited rats. There is also no evidence from other studies that the OFC is necessary for discriminating the sensory properties of cues; rats without OFC or in whom the OFC is inactivated perform well in a number of settings that require them to distinguish different cues to guide responding (Schoenbaum et al., 2002; Boulougouris et al., 2007; Takahashi et al., 2009; Jones et al., 2012).

A second consideration to discuss is the timing of our manipulation and its specificity. We inhibited OFC only during cue presentation, precisely when we previously observed single unit correlates of cue-cue encoding; our design did not include control conditions in which similar inhibition was done before or after the cues or during the intertrial intervals. Thus, while we can conclude that OFC must be online at the time the neural correlates were observed, we cannot conclude that it does not need to be online at any other time during the first phase. Although OFC can be inactivated briefly between trials without affecting OFC-dependent learning and behavior (Takahashi et al., 2013), we would not be surprised if processing outside the strictly defined cue period – say immediately before or after – were also necessary for normal learning. Such a result would not invalidate what we have shown here, but it would show that learning is not fully completed during the external sensory events. While defining this critical period would be very interesting, it would require a succession of control groups that we did not deem practical (just after the cues, 20 s after the cues, 40 s after the cues, and so on).

A third consideration is whether the effect of optogenetic inhibition could reflect something other than the inhibition of the neural correlates demonstrated in our earlier study. While we know from our control group, that simply delivering light during the cue period is not sufficient, perhaps inhibiting OFC neurons during this period distracts the rats, because it is rewarding or punishing or for some other reason. If this were the case, then we would have expected to see an impact of this on learning and responding to these cues in the later periods of the task. We did not see any evidence of this. Further we know from a number of prior studies that brief periods of OFC inhibition, similar to that employed here, often have minimal or no effects on ongoing behavior (Takahashi et al., 2013; Gardner et al., 2017; Gardner et al., 2018). These results suggest this is not, by itself, rewarding, painful or otherwise distracting. Finally, it has been shown that lateral OFC inactivation is not sufficient to produce state-dependent learning, which provides very strong evidence that it does not create a tangible experience in and of itself (Panayi and Killcross, 2014).

A final consideration is that all rats received food cup approach shaping prior to preconditioning. It is possible that this changes the salience of the conditioning chamber context and causes increased attention to the cues during preconditioning, which may facilitate learning. If this is the case, then one interpretation of the current findings would be that OFC is necessary for normal acquisition of the associations during preconditioning because it contributes to this boost in attention, perhaps secondary to a role in processing the value of the context, rather than contributing to the encoding itself. This idea would be consistent with results showing correlates of risk (O'Neill and Schultz, 2010; Ogawa et al., 2013), uncertainty (van Duuren et al., 2009) and salience (Ogawa et al., 2013) in OFC neurons, as well as the finding that OFC value coding is attentionally gated (McGinty et al., 2016) and active in auditory oddball task (Nguyen and Lin, 2014). However, while it is possible that inactivating OFC affected learning of the sensory-sensory associations by interfering with a primary role for OFC in supporting the context or even cue salience, it seems more parsimonious to us to propose that the role OFC plays in supporting salience is secondary to the associative learning role that OFC clearly supports. This idea is consistent with attentional models, both old and new, that link cue salience to associative strength – changes in cue associative strength drive changes in salience (Mackintosh, 1975; Pearce and Hall, 1980; Haselgrove et al., 2010; Esber and Haselgrove, 2011).

Of course, we do not intend to suggest that OFC is the only area that is necessary for this sort of value-neutral sensory learning. This is surely not the case. Indeed even when preconditioning is the readout, we know that interfering with several cortical areas including hippocampus (Port et al., 1987), retrosplenial cortex (Robinson et al., 2011; Robinson et al., 2014; Fournier et al., 2020), and perirhinal cortex (Holmes et al., 2013; Wong et al., 2019) seems to impair the acquisition of sensory-sensory associations. While most cortical and subcortical areas encode variables relevant to predicting biologically-relevant outcomes (Milad and Quirk, 2002; Burgos-Robles et al., 2009; Kennerley et al., 2011; Cai and Padoa-Schioppa, 2012; Burgos-Robles et al., 2013; Giustino et al., 2016; Giustino et al., 2019; Halladay et al., 2020), few studies look at whether the same areas track incidental sensory-sensory associations. Perhaps correlates like those observed in the OFC are ubiquitous; since the organism does not yet understand whether this information is useful it is encoded and is available for some time to enter into relationships reflecting the function of the area. This account would predict that other cortical areas (e.g. prelimbic, infralimbic, cingulate, retrosplenial) will likely also exhibit correlates of incidental sensory-sensory pairings, like OFC, yet unique single unit responses would not be apparent until the probe test, when subjects must infer specific information about the preconditioned cues based on new information acquired during conditioning. Indeed, fMRI correlates of cue-cue learning were observed in precentral gyrus, middle occipital gyrus, insula, and hippocampus in a human sensory preconditioning task (Wang et al., 2020a), and single unit correlates also exist in nucleus accumbens (Cerri et al., 2014). Along similar lines, OFC might contribute something to how the sensory-sensory associations are laid down that is necessary for their subsequent recall for use in the probe test, when it involves appetitive responding, while not being involved more generally in all forms of sensory associations. This could be assessed with fear conditioning.

Lastly we would note that while preconditioned responding has been shown as sensitive to extinction of the conditioned cue in fear conditioning (Rizley and Rescorla, 1972) as well as to aversive conditioning when the conditioned cue is a tastant (Blundell et al., 2003), sensitivity of the preconditioned response to devaluation of the reward predicted by the conditioned cue is novel. This result is important because, while it is conciliant with a mechanism whereby preconditioned responding reflects inference about food in the probe test, it is less consistent with other mechanisms whereby the preconditioned cue has been proposed to acquire value directly through so-called mediated learning in the conditioning phase. Such directly acquired value should leave residual responding that is resistant to devaluation. We did not see any evidence of this, consistent with prior work showing that preconditioned cues trained as we have done here do not acquire value (Sharpe et al., 2017). The demonstration of the devaluation sensitivity of this response nicely supports our contention that its OFC-dependence, both here and in prior work, reflects the role of OFC in using the underlying associative model to infer the likely delivery of food.

All data generated are contained within the source data files for Figure 2 and 3.

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Author details

1. Evan E Hart

   National Institute on Drug Abuse Intramural Research Program, National Institutes of Health, Baltimore, United States

   Contribution

   Conceptualization, Formal analysis, Investigation, Methodology, Writing - original draft, Writing - review and editing

   For correspondence

   evan.hart@nih.gov

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0003-1487-5628

2. Melissa J Sharpe

   1. National Institute on Drug Abuse Intramural Research Program, National Institutes of Health, Baltimore, United States
   2. Department of Psychology, University of California, Los Angeles, Los Angeles, United States

   Contribution

   Conceptualization, Investigation, Methodology, Writing - review and editing

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0002-5375-2076

3. Matthew PH Gardner

   National Institute on Drug Abuse Intramural Research Program, National Institutes of Health, Baltimore, United States

   Contribution

   Conceptualization, Methodology, Writing - review and editing

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0002-9146-5043

4. Geoffrey Schoenbaum

   1. National Institute on Drug Abuse Intramural Research Program, National Institutes of Health, Baltimore, United States
   2. Department of Neuroscience, Johns Hopkins School of Medicine, Baltimore, United States
   3. Department of Psychiatry, University of Maryland School of Medicine, Baltimore, United States
   4. Department of Anatomy and Neurobiology, University of Maryland School of Medicine, Baltimore, United States

   Contribution

   Conceptualization, Supervision, Funding acquisition, Writing - original draft, Writing - review and editing

   For correspondence

   geoffrey.schoenbaum@nih.gov

   Competing interests

   Reviewing editor, eLife

   "This ORCID iD identifies the author of this article:" 0000-0001-8180-0701

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