bioRxiv preprint doi: https://doi.org/10.1101/2021.07.21.453258; this version posted July 23, 2021. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license. Retrosplenial cortex is necessary for spatial and non-spatial latent learning in mice Ana Carolina Bottura de Barros1,2*, Liad J. Baruchin1#, Marios C. Panayi3#, Nils Nyberg1, Veronika Samborska1, Mitchell T. Mealing1, Thomas Akam3, Jeehyun Kwag4, David M. Bannerman3 & Michael M. Kohl1,2* 1 Dept. of Physiology, Anatomy and Genetics, University of Oxford, Oxford, OX1 3PT, UK 2 Institute of Neuroscience and Psychology, University of Glasgow, Glasgow, G12 8QQ, UK 3 Dept. of Experimental Psychology, University of Oxford, Oxford, OX1 3SR, UK 4 Dept. of Brain and Cognitive Engineering, Korea University, Seoul, 136-71, Republic of Korea #These authors contributed equally *Correspondence: [email protected] & [email protected] Keywords: Latent Learning, Retrosplenial Cortex, Optogenetics, Internal Model, Mice 1/19 bioRxiv preprint doi: https://doi.org/10.1101/2021.07.21.453258; this version posted July 23, 2021. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license. 1 Abstract 2 Latent learning occurs when associations are formed between stimuli in the absence of explicit 3 reinforcement. Traditionally, latent learning in rodents has been associated with the creation internal 4 models of space. However, increasing evidence points to roles of internal models also in non-spatial 5 decision making. Whether the same brain structures and processes support the creation of spatially- 6 anchored or non-spatial internal models via latent learning, is an open question. To address this 7 question, we developed a novel operant box task that allows to test spatial and non-spatial versions 8 of a flavour-based sensory preconditioning paradigm. We probed the role of the retrosplenial cortex, 9 a brain area associated with spatial cognition and subjective value representation, in this task using 10 precise, closed-loop optogenetic silencing during different task phases. We show that the 11 retrosplenial cortex is necessary for both spatial and non-spatial latent learning in mice. We further 12 demonstrate that the requirement of retrosplenial cortex is limited to the preconditioning phase of 13 the task. Our results provide insight into the specific role of the retrosplenial cortex in latent learning, 14 demonstrate that latent learning plays a general part in the creation of internal models, independent 15 of spatial anchors, and provide a novel avenue for studying model-based decision making. 16 Introduction 17 Decision making refers to the process of selecting a particular option among a set of alternatives 18 expected to produce different outcomes 1. One way the brain is thought to aid decision making is 19 through updating an internal model 2,3. Such updates may be produced by latent learning, in which 20 information about the causal relationships between stimuli is stored in the absence of 21 appetitive/aversive outcomes. While latent learning was initially thought to help create internal maps 22 of space 4 there is a growing appreciation that it may be also important for creating more general, 23 non-spatial cognitive maps 5,6. Whether different brain regions specialise in supporting spatial or non- 24 spatial forms of latent learning remains an open question. 25 Sensory preconditioning (SPC) can be used to assess latent learning experimentally where two 26 neutral stimuli, A and B, are presented together in a preexposure phase, typically followed by 27 conditioning stimulus B to an appetitive or aversive outcome, before testing the animal’s response 28 to the never-conditioned stimulus A 7. At test, subjects respond to A as if it predicted the outcome, 29 even though they were never explicitly paired. This suggests that latent learning about the 30 associative relationship between A-B resulted in an internal model that, when combined with learning 31 that B -> Outcome, allows for an inference that A-B -> Outcome. 32 Several brain structures have been implicated in rodent SPC, including hippocampus 8,9, perirhinal 33 10,11, entorhinal 5,12 orbitofrontal 13,14 and retrosplenial cortex (RSC) 15–17. The RSC has mostly been 34 associated with spatial cognition 18–22 but may also be involved in processing non-spatial information 35 23–25. This made the RSC an ideal place to test whether latent learning is a broadly employed process 2/19 bioRxiv preprint doi: https://doi.org/10.1101/2021.07.21.453258; this version posted July 23, 2021. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license. 36 that it is used in updating not just spatially anchored models but more fundamentally also models 37 lacking spatial markers. Furthermore, in contrast to previous work 15–17, our task design allowed 38 precise control of foreground and background cues as well as removing possible spatial confounds 39 by not using auditory or visual cues thus allowing us to test spatial and non-spatial versions of the 40 same SPC task while precisely silencing RSC using closed-loop optogenetics. 41 Results 42 A viral construct containing the red-shifted cruxhalorhodopsin, Jaws 26 under control of the CaMKII⍺ 43 promotor (AAV9-CamKII⍺-Jaws-KCG-GFP-ER2) was injected into two sites bilaterally in the dorsal 44 RSC in adult male wild-type mice (Figure 1A). This gave robust expression of Jaws-GFP throughout 45 the dorsal RSC (Supplementary Figure 1). We used 32-contact linear silicon probe recordings in 46 anaesthetised mice to confirm that neurons in the agranular and granular part of the RSC could be 47 silenced by red light delivered for varying durations (150 to 1000 ms) corresponding to those in 48 behavioural tasks (Figure 1B). We compared single unit recordings at different depths of the RSC 49 between groups of Jaws-injected experimental mice and control mice that received equivalent 50 injections of a virus lacking Jaws (AAV5-CamKII⍺-eYFP). We found that activation of Jaws produced 51 temporally precise and reversible silencing of RSC neurons (Figure 1C-H; three-way ANOVA (light 52 x depth x group); interaction of light and group: F(1,18) = 11.348, p = 0.003, main effect of group: 53 F(1,18) = 17.614, p = 0.001; n = 2000 trials from one experimental and one control mouse) and that 54 the efficacy of the optogenetic silencing did not vary with recording depth (three-way ANOVA; all 55 depth interactions F(1,2) < 2.003, p > 0.150). After an initial rebound, activity was not significantly 56 different to controls after around 150 ms. 57 58 Figure 1: Optogenetics enables temporally precise and reversible silencing of retrosplenial cortex (RSC) in 59 vivo. (A) Adeno-associated virus containing the Jaws-KGC-GFP-ER2 (“Jaws”) or e-YFP (“Control”) construct 3/19 bioRxiv preprint doi: https://doi.org/10.1101/2021.07.21.453258; this version posted July 23, 2021. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license. 60 under the control of the CaMKII⍺ promotor was used. Virus was injected into two sites per hemisphere of the 61 RSC (target spread indicated in green; black dotted lines: RSC boundaries). Virus injection resulted in Jaws- 62 GFP or e-YFP expression in the dorsal RSC. (B) A 32-contact silicon electrode was used to record single unit 63 activity before, during and after illumination with red light delivered via an optical fibre. Image shows a fixed 64 section of a brain after recording (Jaws-GFP in green; DAPI in blue; approximate location of electrode based 65 on DiI track in red is indicated; electrode width is not to scale; coloured circles on probe represent the different 66 recording depths shown in panels C-H; white dotted line: boundaries of granular (RSCg) and agranular (RSCa) 67 parts of RSC). (C-E) Illumination of RSC neurons in Jaws-expressing mice resulted in a reversible reduction 68 in spontaneous spiking frequency in RSCa and RSCg. (F-H) Illumination of RSC neurons in GFP-expressing 69 control mice had no effect on spontaneous spiking frequency. Variable duration light ON epoch indicated in 70 red. Representative spike raster for ten neurons at each recording depth as well as normalised mean firing 71 rate for each 50 ms bin are shown. Error bars represent SEM. 72 For behavioural testing, a lightweight red LED 27 was implanted between the four virus injection sites 73 to illuminate RSC (Figure 2A). We verified LED implant placement and the level of viral spread 74 through histological analyses after behavioural testing and confirmed that there were no significant 75 differences in LED placement and viral spread (Supplementary Figure 1). 76 To study the role of RSC in the latent learning of spatial or non-spatial stimulus-stimulus 77 associations, we adapted a flavour-based sensory preconditioning (SPC) task 28 for use in an 78 operant box set-up. Jaws and control groups of mice could obtain small amounts of differently 79 flavoured water from nose-poke ports that were fitted with infrared beam-breaks.