Corticosterone

Chronic exposure to glucocorticoids induces suboptimal decision-making in mice

Lidia Cabeza a,∗, Bahrie Ramadan a, Julie Giustiniani a,b,c, Christophe Houdayer a, Yann Pellequer d, Damien Gabriel a,c, Sylvie Fauconnet c,e,f, Emmanuel Haffen a,b,c,
Pierre-Yves Risold a, Dominique Fellmann a, David Belin g, Yvan Peterschmitt a,∗
aLaboratoire de Neurosciences Intégratives et Cliniques EA-481, Université de Bourgogne – Franche-Comté, Besançon, France
bClinical Psychiatry, Hôpital Universitaire CHRU, Besançon, France
cHôpital Universitaire CHRU, CIC-INSERM-1431, Besançon, France
dPEPITE EA-4267, Université de Bourgogne – Franche-Comté, Besançon, France
eLaboratoire de Carcinogenèse associée aux HPV EA-3181, Université de Bourgogne – Franche-Comté, Besançon, France
fUrologie, andrologie et transplantation rénale, Hôpital Universitaire CHRU, Besançon, France
gDepartment of Psychology, University of Cambridge, Cambridge, United Kingdom
KEYWORDS Decision-making; Corticosterone; Gambling task

Abstract
Anxio-depressive symptoms as well as severe cognitive dysfunction including aberrant decision- making (DM) are documented in neuropsychiatric patients with hypercortisolaemia. Yet, the influence of the hypothalamo-pituitary-adrenal (HPA) axis on DM processes remains poorly un- derstood. As a tractable mean to approach this human condition, adult male C57BL/6JRj mice were chronically treated with corticosterone (CORT) prior to behavioural, physiological and neurobiological evaluation. The behavioural data indicate that chronic CORT delays the ac- quisition of contingencies required to orient responding towards optimal DM performance in a mouse Gambling Task (mGT). Specifically, CORT-treated animals show a longer exploration and a delayed onset of the optimal DM performance. Remarkably, the proportion of individuals per- forming suboptimally in the mGT is increased in the CORT condition. This variability seems to Chronically elevated circulating glucocorticoids (GC) have been extensively shown to have detrimental physiological and cognitive effects (see for instance Wolkowitz et al., 2009). Particularly, persistent hypothalamo-pituitary- adrenal (HPA) axis dysfunction has been reported in humans upon repeated stress, with elevated levels of the endogenous GC cortisol (Marin et al., 2011; McEwen, 2017; Zunszain et al., 2011), but also in pa- tients with chronic inflammatory diseases treated with exogenous GC (Oray et al., 2016; Paragliola et al., 2017; Straub and Cutolo, 2016). In fact, hypercortisolaemia is part of the symptomatology reported in patients with neuropsychiatric disorders afflicted with severe cognitive dysfunction (Gomez et al., 2009; Hinkelmann et al., 2009). Specifically, aberrant decision-making (DM) has been de- scribed in patients suffering from depression using the Iowa Gambling Task (IGT) (Cella et al., 2010). This paradigm involves probabilistic learning via monetary rewards and penalties, and optimal task performance that leads to the maximization of gains, requires subjects to develop a preference for smaller immediate rewards in order to avoid more important losses in the long-term. Interestingly, maladaptive DM strategies have also been reported in healthy subjects (Bechara et al., 1994; Giustiniani et al., 2015). Of particular interest, depressed patients show a reduced ability to detect and incorporate experience from reward-learning associations (Pizzagalli, 2014), therefore anhedonia is thought to act by modifying goal-directed behaviours when positive reinforcements are involved (Must et al., 2013). Moreover, hyposensitivity to positive outcome (reward) and maladaptive responses to negative outcome have been linked to depression (Belzung et al., 2015; Must et al., 2006), suggesting a dysfunctional in- teraction between limbic and motor-executive regions as putative underlying mechanisms. Yet, the influence of the HPA axis on DM alterations remains poorly understood. The regulatory role of GC on HPA axis activity (Smith and Vale, 2006) has pointed to imbalances in the expression of their main receptors (glucocorticoid- GR, and miner- alocorticoid receptors -MR) as biomarkers of depressive states (de Kloet et al., 2018; Zhe et al., 2008). Simul- taneously, the corticotropin-releasing factor (CRF), the major activator of the HPA axis, is thought a key player in stress-induced executive dysfunction (Uribe-Mariño et al.,
Gillespie and Nemeroff, 2005; Zobel et al., 2000).
Chronic corticosterone (CORT) administration in rodents represents a tractable mean to address these human patho- logical conditions (Darcet et al., 2016). In fact, chronic CORT-treated animals exhibit a behavioural spectrum rem- iniscent to emotional anxio-depressive symptoms as evi- denced in several conditioned and non-conditioned tasks (Darcet et al., 2014; David et al., 2009; Dieterich et al., 2019; Dieterich et al., 2020; Gourley et al., 2008; Gourley and Taylor, 2009). Besides, in gambling tasks, healthy rodents efficiently explore and sample from differ- ent options prior to establish their choice strategy upon associative and reinforcement learning, showing a high inter-individual variability, probably shared with humans (Cabeza et al., 2020; Daniel et al., 2017; de Visser et al., 2011; Pittaras et al., 2016; Rivalan et al., 2013, 2009; Steingroever et al., 2013).
Here, we hypothesized that chronic CORT exposure leads to suboptimal DM processing under uncertainty in a mouse Gambling Task. In line with the dimensional frame- work of the Research Domain Criteria Initiative (RDoC) (Cuthbert and Insel, 2010), we addressed feedback sen- sitivity since optimal performance in gambling tasks re- quires effective exploration of options in their early stages (de Visser et al., 2011; Pittaras et al., 2016). Aiming to elucidate their implication in suboptimal DM, spatial work- ing memory (WM) and psychomotricity, as cognitive and arousal-sensorimotor constructs, were also explored. Three relevant brain regions were targeted in this study given their contribution in instrumental behaviour, and mood and stress-related symptomatology: the medial prefrontal cor- tex (mPFC) and the dorsolateral striatum (DLS), modulators of goal-directed and habit-based learning processes respec- tively (Daw et al., 2005; Schwabe and Wolf, 2009), and the ventral hippocampus (VH), involved in stress and emotional processing, exerting strong regulatory control on the HPA axis (Fanselow, 2010). The protein levels of GR, MR and CRF were quantified in these brain areas. As depression is associated with a high rate of pharmacological resistance (Akil et al., 2018; McIntyre et al., 2014) and to a high risk of suicide (Conejero et al., 2018; Hawton et al., 2013), under- standing how neuronal mechanisms underlying DM processes are altered may offer insights towards the detection of pre- dictive biomarkers for treatment selection.

2.Experimental procedures
2.1.Animals
Eighty 6–8 week-old male C57BL/6JRj mice (EtsJanvier Labs, Saint- Berthevin, France) were group-housed and maintained under a nor-mal 12-h light/dark cycle with constant temperature (22±2 °C). They had access to standard chow (Kliba Nafag 3430PMS10, Serlab, CH-4303 Kaiserau, Germany) ad libitum for three weeks, and the fourth week onwards, under food restriction to 80–90% of their free- feeding weight (mean ± SEM (g) = 26.20±0.26). Bottles containing water and/or treatment were available at all times.
Experiments were all conducted following the standards of the Ethical Committee in Animal Experimentation from Besançon (CEBEA-58; A-25–056–2). All efforts were made to minimize animal suffering during the experiments according to the Directive from the European Council at 22nd of September 2010 (2010/63/EU).

2.2.Pharmacological treatment
Mice started being treated four weeks before the beginning of the behavioural assessment. Half the individuals received cor- ticosterone (CORT, -4-Pregnene-11β-diol-3,20–dione-21–dione, Sigma-Aldrich, France) in the drinking water (35 μg/ml mice drank around 3–4 ml/day, therefore equivalent to approximately 5 mg/kg/day, CORT group, n=40). CORT was freshly dissolved twice a week in vehicle (VEH, 0.45% hydroxypropyl-β-cyclodextrin -βCD, Roquette GmbH, France) which control animals (VEH group, n=40) received in the drinking water throughout the entire experiment (David et al., 2009; Mekiri et al., 2017).

2.3.Multi-domain behavioural characterization
Mice were tested behaviourally during the light phase of the cycle (from 8:00 a.m.) from the fourth week of differential treatment.
A timeline of the experiment is presented in Fig. 1, established within the framework of the RDoC to assess the functioning of sev- eral complementary systems, including Negative and Positive Va- lence Systems, Cognitive, Sensorimotor and Arousal and Regulation Systems.

2.3.1.Delayed spatial win-shift task (dWST)
After 5 consecutive training days, spatial WM was tested in a sub- set of animals (VEH, n=22; CORT, n=22) as previously described(adapted from (Furgerson et al., 2014), for details see SOM).

2.3.2.Mouse gambling task (mGT)
Decision-making was measured using the mGT task the protocol of which we have previously described (Cabeza et al., 2020). The task took place in a completely opaque 4-arm radial maze, with identical and equidistant arms, and a common central zone used as a start-point. Mice were rewarded with 20 mg grain-based pellets or punished with grain-based pellets previously treated with qui- nine (180 mM quinine hydrocholride, Sigma-Aldrich, Schnelldorf, Germany). Quinine pellets were not palatable but edible.
Mice were trained twice daily for five consecutive days with each daily session consisting of 20 choice trials (a total of 100 trials per animal). On each trial, positive and negative reinforcers were allo- cated to the arms following a probabilistic rule so that visiting arms A and B was overall disadvantageous while visiting arms C and D was overall advantageous. The former resulted in access to immediate larger reward, but larger cumulative negative reinforce in the long run (9 and 14 rewards per session respectively) whereas the lat- ter resulted in access to smaller immediate reward but a smaller cumulative punishment over time (50 and 66 rewards per session). Mice were placed in their home cages for 90 s between consecutive trials. The location of advantageous and disadvantageous arms was randomized with different reward and punishment sequences for each animal.
Decision-making performance in the mGT was measured as the percentage of advantageous choices over five 20-trial sessions. Choice strategy based on 4 different behavioural dimensions(stickiness, flexibility, lose-shift and win-stay scores), was assessed in 40-trial blocks as previously described (Cabeza et al., 2020; de Visser et al., 2011; Pittaras et al., 2016; Robbins and Cardi- nal, 2019). Performance during the last session was considered for the overall measure of DM performance, as previously described (Rivalan et al., 2013, 2009). Six mice displaying immediate spatial preference amongst options (choice proportion different from the expected in absence of spatial preference, thus 25% of choices for each of the 4 available options; X2 , p<0.05) were discarded from the subsequent mGT analyses (VEH, n=39; CORT, n=35). 2.3.3.Sucrose preference test (SPT) The individual sensitivity to reward (Fouyssac et al., 2020) was measured using the preference for a sucrose solution over water, as previously described (Cabeza et al., 2020). 2.3.4.Forced swim test (FST) Coping strategies in the face of distressing, uncertain conditions were measured in a FST. The switch from an active to a pas- sive coping style i.e. the acquirement of immobility after ini- tial attempts to scape by swimming, struggling and climbing, has been directly associated to a complementary GR and MR medi- ated action of glucocorticoids in the behavioural adaptation to stress-coping (de Kloet et al., 2018; de Kloet and Molendijk, 2016; Molendijk and de Kloet, 2019). Mice were individually placed for 6 min in an inescapable glass cylinder filled with 20 cm of warm water (31.5±0.5 °C) and the overall time during which they were immobile was recorded (Porsolt et al., 1978). Two animals were dis- carded from the analysis due to technical reasons. 2.3.5.Motor learning task (MLT) Psychomotricity was measured using a rotarod task (adapted from (Le Merrer et al., 2013) and detailed in the SOM. All procedures including food reward (20 mg Dustless Preci- sion Pellets R⃝ Grain-Based Diet, PHYMEP s.a.r.L., Paris, France) were preceded by a habituation period inside the home cages (see Fig. 1 for the experimental design). 2.4.Physiological responses to chronic cort treatment 2.4.1.Fur coat state (FCS) Owing to the effects of GC on epidermal homoeostasis (Pérez, 2011) and hair growth initiation (Stenn et al., 1993), the state of the fur coat of each animal was evaluated weekly as an index of pharmaco- logical efficacy and reflecting self-oriented behaviour (Nollet et al., 2013). 2.4.2.CORT plasma assays Final trunk blood samples were collected from all animals (n=80) 5–7 days after the last behavioural test and directly centrifuged at 2100 g for 15 min at 20 °C. Serum was collected and stored at -80 °C until assayed. Plasma CORT concentration was measured us- ing an immunoassay kit (DetectX Corticosterone Immunoassay kit, arbour Assays, Ann arbour, Michigan, USA). In order to measure the homoeostatic stress reactivity of the HPA axis, blood samples were also collected from a subset of mice (VEH, n=10; CORT, n=9) fol- lowing a gentle restraint stress (Benedetti et al., 2012) directly be- fore sacrifice. 2.5.Western-blots Animals were sacrificed by rapid cervical dislocation 5–7 days af- ter the last behavioural test, in the central hours of the light cycle (from 2:00 p.m.). Brains were removed, snap-frozen and stored at-80 °C until processed. Bilateral samples from the mPFC (from 2.3 to 1.3 mm anterior to bregma), the DLS (from 1.1 to 0.1 anterior to bregma) and the VH (from 2.8 to 3.8 posterior to bregma) were ob- tained from 1 mm-thick coronal sections obtained using a cryostat and stored at -80 °C. Samples were processed as described in the SOM with anti- GR (mouse; 1:500; sc-393,232, Santa Cruz Biotechnology), anti- MR (rabbit; 1/1000; ab62532, Abcam) or anti-CRF (mouse; 1:250; sc-293187, Santa Cruz Biotechnology) primary antibodies and HRP anti-Mouse Ig (goat; 1:5000; BD PharmingenTM ) or HRP anti-Rabbit (goat; 1:5000; BD PharmingenTM ) secondary antibodies. Membranes were reprobed with anti-β-actin, which served as a loading control and allows normalization for sample comparison (mouse; 1:1000; sc-47778, Santa Cruz Biotechnology). Western-blot images were acquired either with a Bio-Rad Chemi- Doc XRS+ System (Life-Sience, Bio-Rad, France) or with autoradio- graphic films (Hyperfilm ECL, GE Healthcare, Velizy-Villacoublay, France). All quantifications were made blind to the experimental conditions using ImageJ software (National Institutes of Health, Bethesda, MD, USA) (see Fig. S1). Due to technical issues, some samples were not included in the final analyses, so that final samples sizes were: mPFC, GR/MR n=72, CRF n=53; DLS, GR/MR n=70, CRF n=55; VH, GR/MR n=66, CRF n=57. 2.6.Data and statistical analyses Data are presented as means ± SEM. Statistical analyses were conducted using STATISTICA 10 (Stat- soft, Palo Alto, USA) and figures were designed using GraphPad Prism 8 software (GraphPad Inc., San Diego, USA). The sample sizes were identified a priori by statistical power analysis (G∗ Power software, Heinrich Heine Universität, Dussel- dorf, Germany) with a repeated measures ANOVA (RM-ANOVA) de- sign including 3 groups (between-subject factor), 5 measurements (within-subject factor) and predicted effect size of 0.14, 1-ß=0.8 and α=0.05. Our animal sample is predicted to yield highly repro- ducible outcomes with 1-ß>0.8 and α<0.05. Individuals across pharmacological conditions were clustered in three different groups, namely (1) good, (2) intermediate and (3) poor decision-makers (DMs), with distinct preference for the ad- vantageous options: ≥70% preference, between 70% and 50% pref- erence, and ≤50% preference respectively. Assumptions for parametric analysis were verified prior to each analysis: normality of distribution with Shapiro-Wilk, homogeneity of variance with Levene’s and sphericity with Mauchly‘s tests. Be- havioural time-dependent measures assessed during the mGT, the dWST and the MLT were analysed by RM-ANOVA with session (1 to 5) or 40-trial block (beginning or end) as within-subject factors, and treatment (VEH vs CORT) or clusters (good, intermediate or poor DMs) as between-subject factors. Group’s performance in the mGT was compared to chance level (50% of advantageous choices) us- ing Student t-tests. The degradation of the coat state due to the treatment was analysed by ANOVA with factors being weeks (1 to 13) and treatment (VEH vs CORT). When datasets did not meet assumptions for parametric analyses, non-parametric analyses i.e. Kruskal-Wallis, Wilcoxon or Mann Whitney U tests, were used. Upon significant main effects, further comparisons were performed with Duncan or Bonferroni corrections. The assumption of independent and normally distributed dis- tribution of treatment populations within each cluster was tested with Chi-squared tests (X2 ). Dimensional relationships between be- havioural markers of DM, as measured as final performance (% of advantageous choices in the last session) variable in the mGT and protein levels in the various brain structures under investigation were analysed using Pearson correlations. For all analyses, alpha was set at 0.05 and effect sizes are re- ported as partial η2 (pη2 ). 3. Results At the population level, all mice showed a progressive in- crease in their performance in the mGT over 5 sessions [main effect of session: F4,288 =31.8, p<0.0000, pη2 =0.31]but no general difference was found between groups [treat- ment: F1,72 =2.4, p>0.05, pη2 =0.03] (Fig. 2A). However, further analyses revealed that whereas VEH mice allo- cated their response preferentially towards advantageous options from session 2 onwards [% advantageous choices vs chance, session 1: t38 =1.2, p>0.05, sessions 2–5: t38 >2.5, all ps<0.0000], CORT mice required 20 more trials to im- prove DM [sessions 1&2: t34 <2.7, ps>0.05, sessions 3–5: t34 >4.8, all ps<0.0000]. Thereby this highlights that chronic CORT lengthens exploration and delays the onset of optimal DM performance. We further explored whether chronic CORT could be considered a vulnerabilisation factor to suboptimal DM (Fig. 2B). The majority of individuals displayed the optimal strategy (good DMs). They represent 82.05% of VEH and only 62.86% of CORT animals (session 5 - mean% advantageous choices ± SEM: 82.78±1.25). Individuals from the interme- diate DM subpopulation developed a delayed preference to- wards the advantageous options, without reaching the op- timal strategy. They constitute only 5.13% of VEH whereas 28.57% of CORT mice (60.00±1.38). Poor DMs failed to de- velop a preference for any option and correspond to 12.82% of VEH and 8.57% of CORT animals (39.38±2.58). The dis- tribution of CORT and VEH mice in the three subpopula- tions was compared, highlighting a significant difference (X2 , p<0.0001) which is mainly accounted for by the inter- mediate DMs. In-depth analysis of interindividual variability was fur- ther performed. Decision-making subpopulations learnt at different rates [main effect of group: F2,71 = 21.0,p<0.0000; pη2 =0.37; session x cluster interaction: F8,284 =6.1, p<0.0000, pη2 =0.15] (Fig. 2C). Good DMs (n=54) needed 20 trials to orientate towards the advanta- geous options [% advantageous choices vs chance, session 1: t53 =2.1, p>0.05, sessions 2–5: t53 >6.2, all ps<0.0000], while intermediate DMs (n=12) needed 80 trials [sessions 1–4: Z<2.05, p>0.05, session 5: Z=7.3, p<0.0001]. Unlike the other two categories, poor DMs (n=8) never exhibited a preference [sessions 1–5: Z<2.4, all ps>0.05]. In the last session of the mGT, good DMs performed differently than intermediate DMs [p<0.05, post-hoc], and the latter differently than poor DMs [p<0.05, post-hoc]. Good and poor DMs performed differently from the fourth session [session 4: p<0.05, session 5: p<0.0001, post-hoc]. Fur- ther analyses revealed that, within the good DM cluster, whose individuals developed the optimal performance, CORT treatment delayed the onset of the strategy i.e. the allocation of the responses towards the advantageous options. Good DMs from the CORT group (n=22) performed differently than chance from the third session onwards [sessions 1&2: Z<2.4, p>0.05, sessions 3–5: Z>3.5, all ps<0.01], while in the VEH group (n=32) they differed al- ready from the second session [session 1: t31 =1.2, p>0.05, sessions 2–5: t31 >6.1, all ps<0.0000] (Figure S2). Collec- tively these data indicate that chronic CORT increases the propensity to suboptimal DM performance with an increased proportion of intermediate DMs compared to controls. To infer strategies mediating mGT performance, we stud- ied the evolution of the behavioural dimensions along task progression. Stickiness [main effect of block: F1,72 =54.8, p<0.0000, pη2 =0.43] and flexibility [block: F1,72 =35.4, p<0.0000, pη2 =0.33] scores changed along the task, without significant effect of the CORT treatment [main ef- fect of treatment, stickiness: F1,72 =0.6, p>0.05, pη2 =0.01;
flexibility: F1,72 =3.4, p>0.05, pη2 =0.05] (Fig. 3A, B). Fi- nal stickiness [r=0.669, p<0.0000] and flexibility scores [r=-0.585, p<0.0000] significantly correlate with final mGT performance. Remarkably, a significant effect of the treatment in in- teraction with the time course for the lose-shift score was evidenced [block x treatment interaction: F1,72 =4.7, p<0.05; pη2 =0.06]. At the beginning of the task, all animals were prone to change option after a negative outcome (mean percentage ± SEM of lose-shift, VEH: 72.83±1.89; CORT: 70.97±2.63). At the end of the task, VEH animals were significantly less prone to change after a penalty (64.49±2.59) than CORT animals (72.85±2.75) [p<0.01, post-hoc] (Fig. 3C). Whereas lose-shift scores do not correlate with final mGT performance in CORT animals [r=-0.050, p=0.77], a trend was evidenced for the VEH condition [r=-0.307, p=0.058]. Concerning the win-stay score, all animals more frequently chose the same option after a reward as the task progressed [main effect of block: F1,72 =52.8, p<0.0000, pη2 =0.42], irrespective of the treat- ment [treatment: F1,72 =2.6, p>0.05, pη2 =0.03] (Fig. 3D). Final win-stay scores significantly correlate with final mGT performance [r=0.614, p<0.0000]. At the subpopulation level, good DMs progressively de- veloped and relied on a more rigid and less flexible strategy than intermediate and poor DMs [main effect of cluster, stickiness: F2,71 =7.0, p<0.01, pη2 =0.16; flexibil- ity: F2,71 =4.3, p<0.05, pη2 =0.11]; block x cluster inter- action, stickiness: F2,71 =13.5, p<0.0001, pη2 =0.27; flex- ibility: F2,71 =9.6, p<0.001, pη2=0.21]. Intermediate and poor DMs were equally rigid and flexible in their choices [p>0.05, post-hoc] (Fig. S3A, S3B). Only final stickiness [r=0.551, p<0.0001] and flexibility [r=-0.587, p<0.0000] scores of good DMs significantly correlate with final mGT performance. Concerning the outcome sensitivity, the three DM subpopulations behaved differently along the task [main effect of cluster, lose-shift: F2,71 =0.7, p>0.05, pη2=0.02; win-stay: F2,71 =7.7, p<0.001, pη2 =0.18; block x cluster in- teraction, lose-shift: F2,71 = 6.0, p<0.01, pη2=0.14; win- stay: F2,71 =7.6, p<0.01, pη2 =0.18]. Initially, good and poor DMs more frequently shift after a penalty than intermedi- ate DMs [p<0.05, post-hoc], the latter significantly increas- ing their lose-shift-based strategy along the task [p<0.05, post-hoc]. Final lose-shift scores were not different be- tween subpopulations [p>0.05, post-hoc] (Fig. S3C). Be- sides, good DMs more frequently chose the same option after a reward as the task progressed [p<0.001, post- hoc], becoming significantly different from intermediate and poor DMs [p<0.01, post-hoc] (Fig. S3D). Finally, op- timal DM relies on final lose-shift [r=-0.447, p<0.001] and win-stay scores [r=0.614, p<0.0000] as they corre- late with final mGT performance in good DMs. No effect of the CORT treatment was evidenced for the behavioural dimensions within DM clusters, irrespective of the block [good DMs, stickiness, beginning: U=345.5; end: U=336.0; flexibility, beginning: U=302.0; end: U=290.5; lose-shift, beginning: U=325.0; end: U=238.0; win-stay, beginning: U=350.5; end: U=321.5, all ps>0.05; intermediate DMs, stickiness, beginning: U=9.5; end: U=4.5; flexibility, be- ginning: U=9.0; end: U=8.0; lose-shift, beginning: U=9.0; end: U=10.0; win-stay, beginning: U=9.0; end: U=7.0, all ps>0.05; poor DMs, stickiness, beginning: U=5.5; end: U=3.5; flexibility, beginning: U=2.0; end: U=5.0; lose-shift, beginning: U=2.0; end: U=5.0; win-stay, beginning: U=2.0; end: U=5.0, all ps>0.05].
To better characterize the influence of chronic CORT on DM processes we further addressed its impact on com- plementary behavioural domains within the RDoC frame- work. CORT-treated mice displayed a more passive cop- ing style when facing uncertainty in the FST, with a sig- nificantly longer immobility duration (total time of immo- bility (s) ± SEM: 175.43±10.36) as compared to VEH animals (129.07±9.21) [t76 =-3.3, p<0.01] (Fig. 3E). As DM subpopulations did not differ [F2,70 =0.2, p>0.05, pη2 =0.01](Fig. 3F) and final mGT performance did not correlate with FST scores [r=-0.12, p>0.05], these results sug-gest that the coping style does not primarily influence DM performance.
Both VEH [consumption of sucrose solution vs 50%: t39 =79.3, p<0.00] and CORT [t39 =61.6, p<0.00] mice ex- pressed a strong preference for the sucrose solution com- pared to water (percentage of total sucrose consump- tion ± SEM, VEH: 96.50 ± 0.59; CORT: 94.84 ± 0.73) (Fig. 3G), and no difference between them was evidenced for the sucrose solution consumption [t78 =1.8, p>0.05]. Moreover, DMs categories did not either differ [F2,71 =0.7,
p>0.05, pη2 =0.02] (Fig. 3H), suggesting that DM perfor- mance does not primarily rely on reactivity to positive outcome.
We further investigated whether chronic CORT alters other dimensions required for goal-directed based DM. Chronic CORT did not impact spatial WM [mean effect of treatment, total number of errors: F1,41 =1.8, p>0.05,
pη2 =0.04; task latency: F1,41 =3.7, p>0.05, pη2 =0.08]. However, a learning process was highlighted [session, to-
tal errors: F1,41 =4.8, p<0.05, pη2 =0.10; test latency: F1,41 =5.5, p<0.05, pη2 =0.12] which is accounted for by VEH animals only [total errors: Z=2.8, p<0.01; test latency: Z=3.3, p<0.001], while CORT mice did not improve along the task [total errors: Z=0.5, p>0.05; test latency: Z=1.2, p>0.05] (Fig. 4A, B). Decision-making subpopulations dif- fered in their dWST performance [cluster x session interaction, total number of errors: F2,40 =7.5, p<0.01, pη2=0.27; task latency: F2,40 =5.0, p<0.05, pη2 =0.20], with poor DMs significantly improving through the task [total number of er- rors: p<0.001; task latency: p<0.01, post-hoc], unlike good [total number of errors: p>0.05; task latency: p>0.05, post- hoc] and intermediate DMs, the latter making more mis- takes at the end of the task [total number of errors: p<0.05; task latency: p>0.05, post-hoc]. At the end, only interme- diate and poor DMs were different in terms of total number
of errors [session 5: F2,40 =3.4, p<0.05, pη2 =0.14; p<0.01, post-hoc], but not in task latency [session 5: F2,40 =2.0, p>0.05, pη2 =0.09]. Final dWST scores do not correlate with final mGT performance, which questions the influence of spatial WM on DM processes.
As CORT slowdowns onset of optimal DM strategy, we tested whether motor performance sub-serving execution and exploitation of the mGT was also impacted. Mice im- proved their performance along the task [main effect of ses-
sion: F3,636 =38.5, p<0.0000, pη2 =0.15], with chronic CORT impairing their general MLT performance [main effect of treatment: F1,212 =12.7, p<0.001; pη2 =0.06]. Nevertheless, no significant interaction was found between factors [treat- ment x session interaction: F3,636 =0.9, p>0.05, pη2 =0.00]. When comparing individual sessions, CORT animals hold shorter on the rotor than VEH mice in the first three ses- sions, a difference that disappeared at the end of the task, thus suggesting a delayed learning process in the patholog- ical condition (Fig. 4C). Decision-making clusters did not behave differently during the task [main effect of cluster: F2,211 =0.1, p>0.05; pη2 =0.00] and MLT scores do not corre-
late with final mGT performance [r=0.0497, p>0.05]. These results show that the CORT treatment interferes with motor learning processes, which could impact exploration in the mGT.
We next investigated whether physiological adaptations to chronic CORT could account for differential DM perfor- mance. The FCS appeared significantly degraded in CORT animals from the third week of treatment [main effect
of treatment: F1,890 =448.1, p>0.0000, pη2 =0.33; week: F13,890 =20.1, p<0.0000, pη2 =0.23; treatment x week inter- action: F13,890 =11.5, p<0.0000, pη2 =0.14; from third week of treatment: all ps<0.01, post-hoc]. Decision-making cat- egories did not differ though, neither in VEH [main ef-fect of cluster: F2,36 =1.7, p>0.05, pη2 =0.08] nor in CORT animals [cluster: F2,32 =0.2, p>0.05, pη2 =0.01]. Moreover, FCS scores do not correlate with final mGT performance [r=0.0205, p>0.05].
As expected, terminal blood sample analyses showed sig- nificantly higher basal plasma CORT levels in treated ani- mals (mean CORT level (ng/mL) ± SEM; VEH: 28.18±4.97;
CORT: 79.02±12.41) [t78 =-3.8, p<0.001], and their HPA axis reactivity to a novel acute stress was significantly blunted (VEH: 224.02±35.21; CORT: 70.18±29.97) [post-stress plasma CORT levels, U=10.0, p<0.01]. No signifi- cant differences in CORT levels were evidenced between DM clusters [main effect of cluster: F2,71 = 0.3, p>0.05,
pη2 =0.01]. CORT levels do not correlate with final mGT per- formance [r=-0.1491, p>0.05].
Finally, we focused on the key players GR/MR ratio and CRF from the regions of interest. The mPFC GR/MR ratio value of CORT animals (mean ± SEM: 1.55±0.37) was significantly decreased compared to control animals (2.30±0.55) [U=451.0, p<0.05] (Fig. 5B, C). To disentan- gle the origin of this difference, GR and MR levels were compared separately. While MR levels did not differ be- tween conditions [U=673.0, p>0.05], GR levels were de- creased in CORT animals [U=547.0, p<0.05]. No differ- ences were found in the VH, nor the DLS between condi- tions [effect of treatment, VH: U=447.0; DLS: U=523.0, all ps>0.05]. The three DM clusters do not either differ in their GR/MR ratio, irrespective of the region of inter- est [cluster, mPFC: H2,68 =1.3; DLS: H2,65 =0.3; HV: H2,61 =0.6, all ps>0.05], suggesting that DM performance do not pri- marily depend on homeostatic HPA deregulation at the GR level.
Concerning CRF levels and regardless of the brain area, no significant differences between conditions [ef- fect of treatment, mPFC: U=301.0; DLS: U=311.0; HV:U=405.0, all ps>0.05], nor between DM clusters [clus- ter, mPFC: H2,49 =1.0; DLS: H2,52 =0.3; HV: H2,52 =4.0, all ps>0.05] were evidenced (Fig. 5D). Nonetheless, a signif- icant correlation between the mPFC CRF levels and the final mGT performance of CORT animals was observed [r=-0.5166, p<0.05] (Fig. 5E), suggesting that vulnera- bility to suboptimal DM induced by chronic CORT relates more to CRF signalling deregulation than to GR per se (Figure S4). 4. Discussion The results of this study reveal that several weeks of CORT exposure delays the encoding of the contingencies required to select responding towards optimal DM in a probabilistic gambling task. Inter-individual differences in the capabil- ity to develop an optimal DM strategy were evidenced in the global mouse population and remarkably, the propor- tion of individuals displaying suboptimal DM performance is enhanced upon chronic CORT. The identified chronic CORT-induced suboptimal spatial WM, which seems to be more detrimental to the learning rate than to memory load, could somehow hamper early exploration in the mGT, impending integration of task con- tingencies, in line with preclinical (Bagneux et al., 2013; Hinson et al., 2002; Jameson et al., 2004; Turnbull et al., 2005) and clinical reports (Bourke et al., 2012). Besides, chronic CORT, instead of hindering final performance, slows- down the learning rate in the MLT, a DLS-dependant mo- tor task that does not rely on positive valence systems (Harl et al., 2017), thus evoking clinical psychomotor re- tardation (Bennabi et al., 2013). Additionally, though re- ward sensitivity does not directly account for differential DM performance, learning to cope with negative outcomes is impaired upon chronic CORT. Taken together, these results suggest a CORT-induced hedonic misbalance with differen- tial DM performance better accounted for by a dysregulated negative (lose-shift dimension) rather than positive (win- stay dimension and sucrose preference) valence system. This study disclosed a GR downregulation in the mPFC of treated animals, suggesting that chronic CORT expo- sure may disturb reflective behaviour for optimal planning, and favour suboptimal habit formation, in line with previ- ous studies addressing the role of the mPFC in instrumen- tal behaviour (Schwabe et al., 2008, 2007; Schwabe and Wolf, 2009). Of particular interest, CRF signalling in the mPFC of CORT individuals was found to negatively corre- late with their final DM performance, underlining synergetic effects of CRF and CORT in stress-induced cognitive alter- ations (in line with Chen et al., 2016). Experimental studies in humans have proposed that IGT performance relies on reward sensitivity (Must et al., 2006) though anhedonia measures do not always correlate with task performance (Rizvi et al., 2016). This is the case for our data in reward sensitivity upon chronic CORT. An effi- cient exploration phase in the IGT and therefore in its ro- dent adaptations, would guide the behaviour to a faster stickiness to the optimal choice strategy, that would be- come more independent of the outcome, i.e. more habitual (Balleine and O’Doherty, 2010; Schwabe and Wolf, 2009). The spatial WM and psychomotor deficits observed in our CORT-treated mice could affect primarily action-outcome learning crucial for optimal DM strategies, rather than solely cue processing, and even if they do not directly predict differential DM, they may compromise the transition from goal-directed to habit-based behaviour. Taking in considera- tion the complementary roles of the studied brain structures in instrumental learning (Daw et al., 2005; Hinson et al., 2002; Schwabe and Wolf, 2009), we suggest that the GR downregulation observed in the mPFC of treated animals would primarily entail suboptimal action-outcome encoding over cue processing, yielding action-outcome consolidation especially vulnerable to chronic CORT. This interpretation is in agreement with previous studies reporting negative consequences on cognition upon chronic stress and anxi- ety (McEwen, 2017; Park and Moghaddam, 2017; Reul and Kloet, 1985). Stress has been shown to affect crf signalling, compro- mising the positive valence system (Birnie et al., 2020) and disrupting fronto-striatal cognition (Hupalo et al., 2019; Uribe-Mariño et al., 2016). Together with the present study, these results suggest that high mPFC CRF levels can be considered a neurobiological endophenotype of vulnerabil- ity to suboptimal DM under chronic stress. Corticotropin- releasing factor signalling disruption may hinder mPFC com- putations supporting optimal fronto-striatal cognitive func- tioning, and specifically goal-directed behaviours, and con- tribute to overreliance on the negative valence system to form suboptimal action-outcome learning. This inter- pretation further support the somatic marker hypothesis (Bechara et al., 2005, 2000) and point towards an integral role of CRF. However, previous studies have warned about the dissociable roles of the ventral and dorsal mPFC in DM, especially when behaviour is reward-guided and sensitive to negative feedback (van Holstein and Floresco, 2020). Since we jointly processed ventral and dorsal mPFC struc- tures, further investigations will be necessary to estab- lish the exact contribution of the prelimbic and infralim- bic areas of the mPFC in the CRF signalling upon chronic CORT. The results presented here demonstrate that chronic CORT exposure impedes optimal DM under uncertainty in male mice, impacting mPFC GR and CRF signalling. Manip- ulating the latter to counterbalance overreliance on the negative valence system with suboptimal habit formation, could prove useful to improve coping with risk aversion to- wards rigidification of optimal choices when DM involves overcoming a conflict. In our study, we chose male individ- uals since they have been described as less risky than fe- males, choosing the advantageous options more frequently in other rodent gambling paradigms (van den Bos et al., 2006). Besides this point, published data on females indi- cate that chronic CORT administration is not equally ef- fective in altering their behaviour (Mekiri et al., 2017; Yohn et al., 2019). Future studies will examine the chronic CORT-induced effect in the mGT in females. In sum, this study provides novel insight into the mech- anisms of maladaptive value-based DM caused by chronic exposure to GC, and have important implications for understanding pathophysiological mechanisms in a trans- diagnostic perspective and for identifying alternative pharmacological targets towards precision medicine in biological psychiatry. Role of the funding source This study was supported by grants from the Communauté d’Agglomération du Grand Besançon (LC), which had no role in the study design, collection, analysis or interpretation of the data, writing of the report and in the decision to submit the paper for publication. DB is funded by a grant from the Medical Research Council (MR/N02530X/1) and a research grant from the Leverhulme Trust (RPG-2016-117). Author contribution LC, YP and DF conceived the experimental design with in- put from DB. LC, BR and CH contributed to the data acquisi- tion. LC and YP analysed the data. LC, YP and DB wrote the manuscript. All authors critically revised the work and ap- proved the version to be published. LC, YP and DF agree to be accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved. Conflicts of Interest All authors declare no conflicts of interest. 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