Generalization of fear learning is shaped by inhibitory sensory processing in mice

Domain: biology
Published: 2026-04-03
Editorial outcome: major_revision

Abstract
When an organism learns that a sensory stimulus predicts a threat, the brain’s neural representation of the stimulus somehow incorporates that information into early sensory processing. That altered sensory processing may causally shape the organism’s response to the stimulus. We used contextual fear conditioning in mice to induce odor avoidance that generalized across odors in proportion to their similarity to the conditioning odor. Visualization of odor representations in vivo revealed they were being reshaped by reductions in GABA receptor-mediated inhibitory signaling in the presynaptic terminals of the olfactory nerve and downstream neurons in proportion to the generalized fear of each odor. Locally blocking GABA receptors in the olfactory bulb caused mice to switch from generalizing fear in proportion to similarity to instead overgeneralizing fear to all odors equally. Learning-induced sensory plasticity thus plays a causal role in shaping fear generalization.

Introduction
Fear is adaptive when it is correctly matched to actually or potentially threatening stimuli1-3. However, learned fear can also overgeneralize to situations that do not predict a threat, driving a range of maladaptive sensory, emotional, cognitive, and behavioral outcomes1,4-10. Both stimulus-specific and generalizing fear learning alters the neurosensory representations of potentially threatening sensory stimuli11-15, sometimes very early in sensory processing16-19. While this sensory neuroplasticity is usually interpreted in the context of fear-related perceptual changes20-22, it remains unclear whether fear-induced sensory neuroplasticity plays a causal role in coupling the sensory stimulus to fear and fear-related behavior. Because fear generalization often occurs along sensory dimensions7,42,71, such a role could have important implications for the etiology and maintenance of anxiety disorders2,5.

In the olfactory system, pairing an odor with a shock induces extensive neuroplasticity and perceptual changes in both humans20,23-25 and mouse models26,27. These changes manifest at every level, including the olfactory sensory neurons (OSNs)16,28,29, periglomerular (PG) and mitral cells in the olfactory bulb27,30, and downstream cortices14,31. When mice learn that a specific odor predicts a shock, the odor-evoked OSN output from the nose to the brain becomes larger and more distinct from other odors28, while if the mouse generalizes its fear to other odors then the OSN response is elevated for all those odors32 and the representations become more similar30. It remains unknown how these neurobiological changes occur or whether they play a causal role in odor-evoked fear expression or fear generalization.

OSN axons compose the olfactory nerve, which innervates the surface of the brain’s olfactory bulb in discrete glomeruli corresponding to each olfactory receptor33. Neurotransmitter release from these OSN synaptic terminals is modulated by presynaptic GABA receptors34-37, which are tonically activated by spillover GABA release from local periglomerular interneurons38-40 and rapidly modulate conductance through N-type calcium channels36. Fear learning downregulates GABA receptor expression in OSNs stimulated prior to a footshock29, suggesting that relief of GABA receptor-mediated inhibition of OSN outputs could play a role in instantiating olfactory fear learning and fear generalization by determining which olfactory bulb glomeruli receive fear-potentiated peripheral input. GABA receptor-mediated signaling also shapes the activity of multiple other cell types in the olfactory bulb, including periglomerular interneurons, external tufted cells, and mitral cells, suggesting that GABA receptor signaling could potentially impact not only primary sensory inputs to the bulb but also the local circuitry that shapes responses within and across odorants.

Within the olfactory bulb, different circuits modulate OSN inputs within and between glomeruli, providing a potential substrate for receptor-specific and generalized gain control, respectively22,38. Disinhibition of local inhibitory circuitry during learning is a common motif during associative learning69,70, including in sensory brain regions. In the auditory cortex, for example, fear learning disinhibits a local microcircuit, thus amplifying pyramidal cell responses to the threat-predictive stimulus that are necessary for learning68. Here we test whether odor-cued fear learning can reduce GABA receptor-mediated inhibition of the peripheral olfactory input to the brain’s olfactory bulb and whether local modulation of this inhibition can cause the generalization of conditioned fear.

Results
To test this hypothesis, we trained mice on a generalizing fear conditioning task comprised of three daily conditioning sessions in a chamber scented with the odorant methyl valerate (MV, an ester) where they received 10 mild, randomly timed footshocks over the course of about 10 minutes (Fig. 1a). Subsequent behavioral testing revealed that mice exhibited a significant fear generalization gradient (Fig. 1c), exhibiting maximal immobility when placed in a different chamber scented with MV, less when the chamber was scented with the similar odor butyl acetate (BA, another ester), and still less when the chamber was scented with the dissimilar odor 2-hexanone (HEX, a ketone; one-way repeated-measures ANOVA, F = 75.82, p < 0.001, η2 = 0.78). Control mice placed in these chambers were equally immobile across odors (Fig. 1c), including mice exposed to shocks without odors (F = 1.83, p = 0.18) and mice exposed to odors without shocks (F = 0.46, p = 0.64).

We also evaluated relative fear expression across odors in a more naturalistic context by observing the avoidance behavior of mice placed in a square arena with MV, BA, or HEX in each of the corners (Fig. 1b). Control mice did not avoid any of the corners (Fig. 1d&e; one-way repeated-measures ANOVA, F = 0.53, p = 0.66). By contrast, fear conditioned mice maintained a longer distance from MV and BA, staying closer to the No Odor corner (Fig. 1d; F = 30.6, p < 0.001, η2 = 0.77) and spending more time in the No-Odor and Hex corners (Fig. 1f). We used information theory-derived metrics to compute the relative likelihood of four a priori models given the avoidance data: no fear of odors, exclusive fear of MV, a similarity-based fear generalization gradient, and overgeneralization of fear equally to all three odors (see Supplemental Methods). The similarity-based fear generalization gradient was the most likely model (AIC 14.2), scoring 7.4-fold more likely than overgeneralization to all odors (AIC 18.2), 11.5-fold more likely than MV-specific fear (AIC 19.1), and 29.1-fold more likely than chance (AIC 21.0). By comparison, in non-conditioned control mice the no fear model (AIC 13.0) was far more likely than any of the competing models (AIC range 19.7-28.3). Taken together these data demonstrate that the fear conditioning paradigm induced fear (Fig. 1c) and avoidance (Fig. 1d-f) of MV that generalized to other odors in proportion to their similarity to MV, a classic sensory generalization gradient41,42.

If the fear expression and generalization induced by this conditioning paradigm were causally related to a reduction in GABA receptor-mediated inhibition in the olfactory bulb, then we would expect to see a) smaller effects of olfactory bulb GABA receptor blockade on the response to MV in fear conditioned mice than in odor-only or shock-only control mice, and b) differential effects of GABA receptor blockade within individual mice in neuron populations that respond to MV (smallest effects), BA (moderate), and HEX (largest). These changes should manifest throughout the olfactory bulb circuit (Fig. 2c), including its OSN synaptic inputs (where GABA receptors are most prominent34) the periglomerular interneurons driven by those inputs, and the mitral cell output of the olfactory bulb. To test these hypotheses, gene-targeted mice conditionally expressing the fluorescent calcium indicator GCaMP6f underwent in vivo optical neurophysiological assessment of odor-evoked neural signaling in populations of OSN terminals, PG cells, and mitral cells of the brain’s olfactory bulb (Fig. 2a). Following fear conditioning (or non-conditioned behavioral control) and behavioral testing of fear responses (Fig. 1a), calcium signals evoked by presentation of each odor were measured from the olfactory bulbs of each mouse before and after the sub-dural application of the GABA receptor antagonist CGP35348 (or vehicle control) to the exposed dorsal surface of the olfactory bulb. Mice were anesthetized to permit open skull experimentation.

Local blockade of GABA receptors caused an immediate increase in odor-evoked calcium signaling pooled across all mice and all odors (Fig. 2b; one-way ANOVA, F = 2860.17, p < 0.001, η2 = 0.64)38. In control mice that received odor alone- or shock-alone exposures, the effect of GABA receptor blockade was nearly identical across odors in OSNs (Fig. 2d, CGP), PG cells (Fig. 2e, CGP), and mitral cells (Fig. 2f, CGP). However, for mice in which MV had been paired with shock the effect of GABA receptor blockade was strongly odor-dependent in all three cell types: OSNs (Fig. 2g; odor by training interaction: F = 20.16, p < 0.001, η2 = 0.07; main effect of odor: F = 11.10, p < 0.001, η2 = 0.04), PG cells (Fig. 2h; interaction: F = 15.49, p < 0.001, η2 = 0.02; odor: F = 51.94, p < 0.001, η2 = 0.06), and mitral cells (Fig. 2i; interaction: F = 19.2, p < 0.001, η2 = 0.02; odor: F = 75.2, p < 0.001, η2 = 0.09). The response to the dissimilar odor HEX was comparable between fear conditioned mice and non-conditioned control mice (Fig. 2d-i, black vs threat-predictive odor MV (Fig. 2g-i, purple) and an intermediate effect was observed for the similar odor BA (Fig. 2g-i, blue). These effects are summarized in Fig. 2j, showing a) that odor-cued fear conditioning causes a reduction in GABA receptor-mediated inhibition that is greater for odors more similar to the CS and b) this fear learning changes odor-evoked activity across the whole olfactory bulb circuit.

Pooling across mice and odors, we observed a significant negative correlation (Pearson’s r, r = -0.33, p < 0.05) between the size of the physiological effect of GABA receptor blockade and the time spent freezing during behavioral testing (Fig. 2k). For non-fear evoking odors in OSNs, the size of the GABA receptor blockade effect generally increased over time within a 7-sec odor presentation (Fig. 2l, HEX), but this effect was absent for the threat predictive-odor (Fig. 2l, MV). In all experiments, vehicle application was associated with a small (~5%) reduction in odor-evoked response, likely attributable to response rundown in these post-durotomy experiments.

Generalization of learned responses from one sensory stimulus to another is classically thought to derive from shared elements in the neural representation of similar stimuli43. For OSNs and PG cells these elements would be individual glomeruli on the surface of the olfactory bulb, each of which corresponds to a population of OSN inputs expressing a particular odor receptor in the nose33. We thus asked whether the fear-associated reduction in GABA receptor-mediated inhibition for BA or HEX would be more pronounced in the glomeruli that were also driven by MV. For OSNs, these jointly-responsive glomeruli (which compose the overlapping elements in the glomerular representation of MV with BA or HEX; Fig. 3a), indeed demonstrated significantly less effect of GABA receptor blockade in fear conditioned mice than glomeruli that responded only to BA or HEX (Fig 3c, one-way ANOVA, F = 9.56, p < 0.01, η2 = 0.084). This confirms that some of the neural generalization of the fear-related change in GABA signaling from MV to BA is indeed due to overlapping elements in the OSN representation of these odors. However, fear learning also somewhat reduced GABA receptor signaling in OSNs in glomeruli that didn’t respond to MV at all, with a lesser effect than those that did (Fig 3c, non-overlapping vs non-conditioned controls), suggesting that direct overlap with MV was not the only mechanism of generalization in OSNs. In PG cell populations, the effect of overlapping glomeruli resembled the effect in OSNs (Fig. 3d; one-way ANOVA, F = 6.41, p < 0.05, η2 = 0.035). Mitral cell responses were too spatially diffuse to perform this analysis reliably.

Another potential mechanism contributing to fear generalization across odors could be spatial proximity of the neurons representing the odors (Fig. 3a), independent of any overlap in the set of neurons responding to each. This was especially of interest in mitral cells, whose secondary dendrites interconnect across long distances in the olfactory bulb. We thus measured the physical distance between each odor-responsive region of interest (ROI) and the ROI that was maximally responsive to MV during imaging of mitral cell populations. As expected, BA-responsive ROIs were closer to the MV maximum than the HEX-responsive ROIs were (Fig. 3b). MV and BA ROIs within 400 µm (roughly four glomerular widths) of the MV response maximum showed a smaller increase after GABA blockade, in HEX ROI however, this effect was not present (Fig. 3e; two-way ANOVA, interaction F = 12.00, p < 0.001, η2 = 0.012, effect of distance F = 33.14, p < 0.001, η2 = 0.033). This suggests that the effects of fear learning we observed on GABA-mediated communication were most pronounced near the loci of CS+ activity in mitral cell signaling. Together, these findings suggest that spatial proximity to key regions of neural activity may be playing a significant role in shaping fear generalization through localized changes in GABA signaling.

To test whether GABA signaling in the olfactory bulb might play a causal role in the expression and generalization of odor-evoked fear, we implanted bilateral cannulae into the olfactory bulbs and infused GABA receptor antagonist (1 mM CGP35348), GABA receptor agonist (1 mM baclofen), or vehicle control before testing their odor avoidance behavior. First, we asked whether intrabulbar GABA receptor modulation would induce fear or odor avoidance in non-fear conditioned mice. Mice who underwent control training paradigms (odor alone or shock alone) and vehicle control infusions before testing explored the arena freely and spent similar amounts of time in each zone of the arena (Fig. 1e). Mice who underwent the control training paradigms but received intrabulbar infusions of GABA receptor antagonist (Fig. 4b) or agonist (Fig. 4c) behaved no differently than those receiving vehicle infusions (Fig. 1e), with no significant differences in overall mobility (one-way ANOVA, F = 3.20, p > 0.05). This demonstrates that GABA receptor modulation by itself does not induce fear behaviors like immobility or odor avoidance at these concentrations.

Next, we asked whether intrabulbar inhibitory signaling might influence the expression and generalization of previously learned fear. In control experiments, mice that received MV-cued fear conditioning and vehicle infusions were just as active as non-conditioned control mice (t = 0.58, p > 0.05) but exhibited a fear generalization gradient centered on MV as described above (Fig. 1c, d, &f; Fig. 4d&e). However, when we artificially expanded the fear learning-induced reduction in GABA receptor signaling to affect all three odors by infusing the GABA receptor antagonist into the olfactory bulb immediately before testing, fear conditioned mice overgeneralized their fear, avoiding all odors. They stayed significantly closer to the unscented corner and farther from the scented corners (Fig. 4f&g), and they avoided HEX just as strongly as MV and BA, spending much more time in the unscented corner and much less time in the HEX corner and the HEX-NO ODOR side of the arena (Fig. 4c-e, h). The best fitting model for odor avoidance in fear conditioned, GABA receptor-blocked mice was the overgeneralization model (equal fear of all odors; AIC 11.7), which was 844 times more likely than the generalization gradient model (AIC 25.2) that best described the vehicle control data (Fig. 1 & 4d), while all other competing models were even less likely (AICs 26.7-27.2). This strongly contrasted with the mice who received the GABA receptor antagonist after behavioral control treatment (Fig. 4b, gray), with the no fear model (equal time in all zones) fitting the data five orders of magnitude better than any other model (Supplemental Data). This demonstrates that the effect of GABA receptor blockade is specific to generalization of fear rather than general odor avoidance.

Finally, we asked whether stimulating GABA receptors in the olfactory bulb might reduce fear expression and generalization in olfactory fear conditioned mice by infusing the GABA receptor agonist baclofen. We observed generally opposite effects to blocking these receptors using CGP35348 in fear conditioned mice (Fig. 4c). Fear conditioned, baclofen-infused mice spent somewhat less time in the unscented corner (Fig. 4c-f, h) and more time near BA than vehicle-infused mice. However, they nonetheless exhibited clear avoidance of MV and BA compared to non-conditioned, baclofen-infused mice (Fig. 4c, blue). Their avoidance behavior was not well-described by any of our a priori models (AIC > 22), but the MV-specific fear model and no fear model were both much more likely than either fear generalization model (Supplementary Data). Overall, mice receiving baclofen infusions exhibited less generalized fear than vehicle controls and behaved more similarly to the unconditioned control mice.

Because the effect of intrabulbar infusion of baclofen in fear conditioned mice was to reduce behavioral discrimination among odors, we performed an additional test to confirm that this dose of baclofen did not impair perceptual discrimination between these odors. Mice were implanted with bilateral intrabulbar cannulae and underwent a habituation/dishabituation test in which mice spontaneously discriminate between a repeatedly presented odor and a novel odor. Each mouse was tested twice, receiving either baclofen or vehicle control infusion prior to testing in randomly assigned order. All mice exhibited decreases in odor investigation across the four habituation trials followed by spontaneous increases in odor investigation upon odor switch (Fig. 5c). Two-way repeated measures ANOVA revealed a significant main effect of trial sequence as expected (F = 27.5, p < 0.001; Greenhouse-Geisser corrected), reflecting the habituation/dishabituation sequence (Fig. 5c). There was no significant main effect of drug (F = 0.82. p = 0.408) or drug x trial-type interaction (F = 1.022, p = 0.420). These data demonstrate that despite the reduction in olfactory signaling induced by baclofen36, mice in these behavioral experiments detected and discriminated among the test odors comparably to control animals.

While baclofen had no significant effect overall there was modest, statistically non-significant evidence that baclofen might increase odor habituation relative to vehicle infusion on the fourth odor presentation (Holm-Bonferroni post-hoc testing; df = 20; p = 0.110) prior to a similar or stronger dishabituation on the subsequent odor-switch trial. This suggests that if anything baclofen served to increase odor discrimination.

Methods
Mice. The study used a total of 121 adult mice (68 male and 53 female) on a C57BL/6J background, aged between 3 and 9 months. To image calcium changes, cre recombinase-mediated conditional expression of fluorescent GCaMP6f62,63 was employed in cells expressing the Tbet gene (for mitral cells, a.k.a. Tbx21), the omp gene (for OSNs), and the gad2 gene (for PG cells). These transgenic lines were bred and crossed in-house. Non-imaged animals were either from the same batch or wild-type mice of the same C57BL/6J strain (Jackson Laboratories). All subjects were housed at 21°C with 40–60% relative humidity under a 12-hour light/dark cycle with ad libitum access to food and water. The work was performed in compliance with protocols approved by the Rutgers University Institutional Animal Care and Use Committee (IACUC, protocol #09-022).

Apparatus. Training cages measuring 10x10 inches (Coulbourn) with shock floors and transparent walls were used, modified for contextual specificity. The open-field setup consisted of a custom-built 18x18-inch box with white matte walls and floor, with mesh metal tea strainers suspended in each corner to hold cotton balls with odors. Animals were recorded using a fish-eye lens camera (Opto). Infusions were performed using an infusion tube (Plastics 1) connected to a syringe pump (Harvard Apparatus). Custom cannulas (Plastics 1) included double guide cannulas (1.4 mm), dummy cannulas (protruding 0.15 mm), infusion cannulas (protruding 0.25 mm), and dust caps. Calcium imaging was conducted with a custom-built microscope using an Olympus 4x objective (0.38 NA) and blue LED illumination. Images were captured at 50 Hz with a RedShirtImaging SM-256 CCD camera, providing a resolution of 256x256 pixels.

Experimental design. The study had three different testing conditions, the subjects either underwent calcium imaging (n = 49, ages 3 to 9 months old) with prior mobility testing, they were tested in the open field (n = 66, ages 3 to 6 months), or they were used in the habituation/dishabituation experiment (n = 6, ages 3 to 6 months). The first experiment used a 3x3x2 design; cell type, training condition, and drug. The training conditions were paired (received both shock and CS+, n = 23), shock only (received only shock but not CS+, n = 13) and odor only (received only CS+ without any shocks, N = 13). The animals have experienced three different odors during the behavioral testing and imaging sections; methyl valerate (CS+), butyl acetate (a similar odor to CS+, both fruity-smelling ester), and 2-hexanone (quite different from the CS+, a chemical-smelling ketone). The CS+ odor was methyl valerate in all training conditions. Subjects were also divided into two drug condition groups according to what type of solution was applied on top of the olfactory bulb halfway through the imaging sessions; 28 of the subjects received 1mM CGP 35348 dissolved in Ringer’s solution while the remaining (n = 21) received vehicle (Ringer’s solution). The open field subjects (n = 66) also underwent the same training paradigm, but they received CGP 35348 (n = 22), baclofen (n = 22) or vehicle (Ringer’s, n = 22) infusions into their olfactory bulbs prior to testing. The experimenter was blind to the contents of all infusates.

Training and testing. Fear learning was established using two visually distinct contexts. Context A (training) featured red dots on opaque white glass, a vertically lined shock floor, and a red drop tray. Context B (used only for calcium imaging) had transparent glass walls, blue stripes, visually different floors, and a gray drop tray. The animals who received the training were kept at separate housing shelves or had other cages in between, this was done to prevent any external learning from happening because of the visible stress of animals nearby. For the first three days, mice were placed in Context A without any stimuli for context pre-exposure. On the next three days, they were again placed in Context A, but this time with their group-specific stimuli. During training, the CS+ odor (methyl valerate) was always present in the context. Two hundred microliters of methyl valerate were applied to a cotton ball with a half-inch diameter, which was placed in a small weighing boat positioned between the shock floor and the drop tray. (During context pre-exposure, the weighing boat and cotton ball were placed in the same position without any odor.) Mice in the US groups (paired and shock-only) received 10 mild shocks (0.3 mA) at random intervals (40-80 seconds). On the seventh day, calcium imaging animals were tested in Context B. Testing sessions included three sets of 120 seconds, each with a different odor: methyl valerate, butyl acetate, or 2-hexanone. The order of odor presentations was randomized via a code to avoid matching the imaging order. The first 30 seconds of each session were excluded from analysis, assuming the animals were still adjusting to the environment. During the remaining 90 seconds, their movements were recorded to calculate the percentage of immobile time. Open-field animals were tested after drug infusions (see Surgery and Infusion Parameters). Within the open-field box, a different odor was placed in each of the four corners. As in training, a cotton ball treated with 200 microliters of pure odor was placed inside a 2x2-inch metal tea bag hung in each corner. The odors included methyl valerate, butyl acetate, 2-hexanone, and no odor. Methyl valerate and butyl acetate were always placed in adjacent corners to create a “danger zone,” while 2-hexanone and the no-odor corner formed a “safe zone.” Animals were free to explore the box for five minutes, after which they were returned to their individual cages.

Surgery and infusion parameters. In the calcium imaging group, mice underwent surgery on the same day, a few hours after behavioral testing, to minimize the impact of the testing experience on plasticity. Mice were anesthetized using pentobarbital (10 mg/kg) administered intraperitoneally, and their scalps were shaved in preparation for surgery. Body temperature was maintained at 38 ± 0.5°C throughout the procedure. To reduce mucus secretion and brain swelling, atropine (100 mg/kg) and dexamethasone (3 mg/kg) were administered, respectively. Additionally, 0.25% bupivacaine (0.25 mL) was applied as a local anesthetic before scalp removal. The periosteal membrane was scraped off, and 70% ethyl alcohol was applied to dry the skull. To ensure stability, the thickest part of the skull was drilled slightly using a coarse dental bit to create a shallow burrow for the adhesive. The mouse’s head was fixed in place using a head bar, super glue, and dental acrylic. A well-like structure was built around the olfactory bulb using dental acrylic to hold the vehicle or drug in place. Before craniotomy, the bone over the olfactory bulb (both sides) was thinned with a coarse dental bit. One side of the bulb remained intact as a control. For the drilled side, a cooled Ringer’s solution was used during the operation to prevent overheating and to avoid air contact with the dura mater. A piece of bone covering approximately 70%-80% of the area was removed using an inlay prep burr. After the dura mater was exposed, a microscopic incision was made using a handmade dura hook (a slightly bent 30-gauge needle), and the dura was carefully removed with fine-tipped forceps. Any bleeding was controlled with surgical foam, and cleaning was kept minimal to avoid damage to the exposed brain. A glass coverslip was placed over the exposed area, floating on the Ringer’s solution, before imaging.

For the open-field and habituation/dishabituation groups, cannula insertion surgery was performed before training65. The procedure followed the same initial steps as described above. Two reference points were marked parallel to the center of the olfactory bulb, where drilling was performed. Guide cannulas were inserted into these drilled holes along with dummy cannulas and dust caps. The exposed skull was encased in acrylic solution. Animals were given 1 mL saline and 10 mg/mL carprofen for recovery and allowed 2-4 days of rest before training. Before testing, animals were anesthetized with isoflurane, and infusion tubes were inserted into their guide cannulas to deliver CGP 35348, baclofen, or vehicle (Ringer’s solution) for open-field animals and baclofen or vehicle for habituation/dishabituation animals. For vehicle-treated animals, 2 µL of Ringer’s solution was infused over one minute. For experimental animals, 2 µL of either 1 mM CGP 35348 or 1 mM baclofen in Ringer’s solution was infused using the same protocol. After infusions, animals rested for 20 minutes before testing.

Habituation/dishabituation behavioral test. To evaluate odor discrimination in baclofen-infused mice, we used a habituation/dishabituation paradigm, designed based on a previously established protocol77. Each mouse (n = 6) was tested under both baclofen and vehicle infusion conditions on separate days, with 2-6-day interval between tests. On each test day, mice received an infusion of either baclofen or vehicle, followed by a 20-minute rest period before testing. The experimenter remained blind to the solution type used for infusion throughout all procedures. Mice were tested in a clean home cage measuring 5x7x11.5 inches and were video recorded using a fish-eye lens camera (Opto) positioned 5 inches over the cage. Each session began with a single presentation of a blank tea strainer containing a cotton ball treated with 0.6 mL mineral oil to habituate the mouse to the stimulus presentation method. This was followed by thirteen 50 sec presentations of 0.6 mL pure odorant delivered on a cotton ball placed in a mesh metal tea strainer manually positioned in the center of the wire cage top. Each trial was separated by five minutes. The trial sequence included 4 trials each of three test odors (MV, BA, and HEX), and a final trial of the 1st odor, yielding 6 possible odor sequences randomly assigned across mice. Video recordings were manually scored by an experimenter blind to the experimental condition. Investigation time on each trial was defined as time spent in a rearing, nose-upward posture anywhere in the cage.

Optical imaging. The optical imaging preparation28,66 was performed as follows. After surgery, subjects were placed under the camera setup mentioned earlier. Odor delivery was controlled through an odor tube positioned directly in front of the animal’s nose. A MATLAB (MathWorks, R2019a) code managed the odor delivery system, which provided nitrogen (odor carrier), ultra-zero air (dilution), and the target odor. The odor concentration and dilution parameters were determined by computer-controlled mass-flow controllers. The first step of each imaging session was to compare the odor-evoked signals on the two sides of the olfactory bulb (thinned vs. durotomy side). If an imbalance was observed due to surgical complexity, the animal was returned to the surgery area, and the same surgical procedure was performed on the intact side. Minor to moderate damage or bleeding that did not affect signaling was overlooked. Where necessary, the exposed area was washed with Ringer’s solution between trial blocks to avoid bleeding. Each trial consisted of 4.5 seconds of pre-odor baseline, 7 seconds of odor stimulation, and 8.5 seconds of post-odor period, resulting in a total trial duration of 20 seconds (1,000 frames at 50 Hz: 225 pre-odor, 350 odor, 425 post-odor). Each trial block contained 8 trials: the first 4 were mock odor presentations at 2% strength to minimize novelty effects, while the last 4 were recorded for analysis. Animals were kept under anesthesia with boosters administered as needed. To avoid interference with the imaging process and breathing, the boosters were given in smaller amounts (~0.01-0.02 mL vs. ~0.05 mL) but at more frequent intervals (~15 minutes vs. ~30 minutes). Boosters were administered before mock trials, and these trials were excluded from analysis. The imaging sessions involved the same three odors used during behavioral testing: methyl valerate (CS+), butyl acetate (similar), and 2-hexanone (different). Six trial blocks were performed for each animal: three during the baseline period and three following drug application. Trials were separated by 60-90 second inter-trial intervals. After three baseline trial blocks, the Ringer’s solution on the exposed bulb was removed with a transfer pipette and replaced with either CGP 35348 (1 mM in Ringer’s) or vehicle (Ringer’s). The same trial structure was repeated after drug application. The experimenter conducting the imaging was blind to the drug condition.

Data analysis and visualization. Imaging data were analyzed using custom-written codes28,89 with additional scripts for spatial pattern analysis. Folder and filenames were automatically shuffled and randomized to ensure the experimenter was blind to the experimental conditions during analysis. Data processing was performed using MATLAB (R2019a) and Python (v3.8). Odor-evoked fluorescence responses (∆F) were calculated by subtracting the mean baseline fluorescence (signal within 1 second before the start of odor presentation) from the fluorescence level in each frame. The normalized value (∆F/F) was obtained by dividing ∆F by the baseline fluorescence. Before analyzing individual trials, glomerular regions of interest (ROIs) were manually selected using average maps from each animal. For mitral cells, regions with shapes resembling glomeruli were selected because their deeper location resulted in fuzzier signals. Each animal and odor combination had its own unique set of ROIs. For each trial and ROI, peaks in odor-evoked signals and their spatiotemporal specifics were identified and averaged. The main dependent variable was the percentage increase in ∆F/F from pre-drug to post-drug for each ROI. For spatial analyses, the location of each ROI was calculated to evaluate overlap and proximity. Overlap was defined as CS- ROIs located within 70 µm (average size of a small glomerulus) of CS+ ROIs in each animal. Proximity was determined by calculating the Euclidean distance of each CS- ROI from the max ∆F/F CS+ ROI for that animal. ROIs were further categorized based on whether they were within 400 µm (approximately the diameter of four glomeruli) of the CS+ ROI or farther away. For temporal analyses, the post-odor presentation fluorescence signal of each ROI was divided into four 2-second intervals. The maximum ∆F/F value within each interval was calculated. Behavioral data were analyzed using EthoVision software (XT 14). Pre-imaging mobility analysis was conducted to calculate the percentage of immobile time for each animal. To confirm fear learning and generalization, paired animals that did not exhibit specific aversion were excluded from imaging. The exclusion criterion required at least a 5% immobility difference between the CS+ odor and other odors. These percentages were then used to assess fear learning and generalization, as well as to correlate behavioral findings with imaging data. For open-field animals, two main analyses were conducted: time spent in different zones and the average distance from specific corners. The open-field arena was divided into 9 equal square zones, including odor zones, intermediate zones, and the center. The time spent in each zone was determined based on the animal’s center point in the video. All statistical analyses were performed in RStudio (v2024.02.0), and graphs were created using Python (v3.8) and Adobe Illustrator (2025). Illustrations were drawn using bioRender and Adobe Photoshop (2025).

Peer review rounds
[{"round": 1, "reviewer_comments": {"reviewer_1": "This study by Bakir et al. investigates the role of the early olfactory system in fear learning by examining activity in olfactory\nsensory neurons (OSNs), mitral cells (MTs), and periglomerular (PG) cells within the olfactory bulb (OB). By manipulating\nGABA receptor activity through the use of an antagonists and an agonist, the authors demonstrate that inhibitory processing\nin the early olfactory pathway plays a critical role in fear learning and, potentially, early memory formation. This finding\nsignificantly extends previous work on sensory disinhibition—particularly in the primary auditory cortex—by demonstrating a\nsimilar mechanism in early olfactory areas. The study is methodologically rigorous, and the results largely support the\nauthors' conclusions. However, I offer several suggestions for further strengthening the manuscript:\n1. Conceptual framing: To broaden the theoretical context, the authors could integrate earlier work on disinhibition in the\nauditory cortex. Specifically, the following studies may be useful in anchoring the current findings within a broader\nframework for associative fear learning and memory:\no Letzkus, J. J., Wolff, S. B., & Lüthi, A. (2015). Disinhibition, a circuit mechanism for associative learning and memory.\nNeuron, 88(2), 264–276.\no Letzkus, J. J., Wolff, S. B., Meyer, E. M., et al. (2011). A disinhibitory microcircuit for associative fear learning in the auditory\ncortex. Nature, 480(7377), 331–335.\n2. Result interpretation: The pharmacological manipulation in the olfactory bulb affects multiple cell types (OSNs, PG cells,\nand MT cells), making it difficult to isolate the causal role of OSNs in fear learning. While the title appropriately avoids\nspecifying OSNs, the Introduction places almost exclusive emphasis on them, and the Discussion does not sufficiently\nexplore alternative explanations involving PG or MT cell contributions. A more balanced consideration of these possibilities\nwould strengthen the overall interpretation.\n3. Fear generalization: While the generalization gradient observed is compelling, the data do not conclusively rule out the\nalternative interpretation that disinhibition directly influences fear learning and only secondarily affects generalization. This\ndistinction could be more clearly addressed in the discussion.\n4. Figure presentation (minor point): Some figure captions would benefit from additional explanation to help readers interpret\nthe results more effectively without referring back to the main text.", "reviewer_2": "Bakir et al. investigated the neural mechanism underlying fear generalization using an odor (CS+)-mediated, contextual fear\nconditioning paradigm in mice. The authors show that odor fear conditioning induced fear responses (immobility) and odor\navoidance in an open field arena, which can be generalized to other odors based on their similarity to the CS+ odor. This\ngeneralization is linked to overlapping and spatial proximity within the olfactory bulb activation map. The authors further\nshow that fear generalization is regulated by GABAB receptor signaling in the olfactory bulb via pharmacological\nmanipulations. Blocking GABAB receptors with an antagonist in fear-conditioned mice leads to broader fear generalization\nto other odors, while infusion of a GABAB agonist shows reduced fear generalization. The authors demonstrate that\ndownregulation of GABAB receptor-mediated inhibition enhances fear generalization via representational plasticity rather\nthan sensory confusion. The overlap and spatial relationship between glomerular responses to different odors underpin the\nspread of fear. Given the conserved role of GABAB signaling across sensory systems, these results suggest a broader\nrelevance for understanding mechanisms underlying generalized anxiety disorders. The study is well-designed with\nappropriate controls and statistical analyses and is clearly written. The manuscript would be further improved if the following\nconcerns were addressed.\nMajor:\n1. Activation of GABAB receptors in the olfactory bulb with baclofen is expected to reduce glutamate release from OSNs.\nTherefore, baclofen-induced behavioral effects shown in Fig. 4 could be potentially due to altered odor\ndetection/discrimination, but not failed fear generalization to other odors. Olfactory bulb imaging experiments (parallel to\nthose shown in Fig. 2B-I for the GABAB antagonist) and/or behavioral tests to show that mice can still distinguish the three\nodors would help to rule out this possibility and further strengthen the conclusions.\n2. In addition to the OSN axon terminals, GABAB receptors are also expressed in other cell types in the olfactory bulb. The\nauthors should discuss potential contributions from other cell types to fear generalization after exogenous application of\nGABAB agonists and antagonists.\nMinor:\n1. Both male and female mice are used in the study. Is there a sex difference observed in the mouse behavior? It would be\nhelpful to use different symbols for male and female mice in Fig. 1C. For example, use x for males and circles for females.\n2. In all figure legends, the animal numbers and trial numbers should be provided wherever applicable.\n3. In reporting one-way ANOVA results, n2 or η² is used in different places to represent eta-squared. Please make it\nconsistent throughout.\n4. In Figure 2 or Figure 3, it would be helpful to show examples of ROIs. This will help readers to appreciate how much\noverlap there is across the activation patterns induced by different odors.\n5. In Fig. 2C, suggest using “OSN Somas” instead of “OSN Bodies”.\n6. In Fig. 2B, in the label “BEHAVIOR CONTROL (CS+)”, there is no CS+ odor in the control groups. Suggest removing\n“CS+” but using MV (the odor name instead). Please define RLI in the figure legend.\n7. Page 5. Last sentence. “odor-evoked responding”, suggest changing to “odor-evoked response”.\n8. Description of Fig. 3A legend seems inaccurate. It states “…across the dorsal bulb for MV (2nd row) are closer to BA (3rd\nrow) than to HEX (bottom)”, while all three images are in the same row.\n9. Page 11. “…OSN inputs to the bub”, where “bub” should be “bulb”.\n10. On page 7, “… the effect of overlapping glomeruli resembled the effect in OSNs (Fig. 2D, ...”. It should be Fig. 3D instead\nof Fig. 2D.\n11. In Fig. 4E legend, “with color scale bar a right” should be “…at right”.", "reviewer_3": "I co-reviewed this manuscript with one of the reviewers who provided the listed reports. This is part of the Nature\nCommunications initiative to facilitate training in peer review and to provide appropriate recognition for Early Career\nResearchers who co-review manuscripts."}, "author_response": "RESPONSE TO REVIEWERS\nWe are grateful to the reviewers and the Editor for their kind words regarding the quality and\nimpact of this work, and we thank them for their helpful comments. We have made targeted\nrevisions throughout the text, including the incorporation of data from a new control experiment\nand the addition of new discussion to incorporate reviewer suggestions regarding cell type-\nspecific contributions and disinhibitory circuit mechanisms for learning in other systems. We\nhave also made clarifying updates to figures and captions. These changes are detailed below.\nReviewer #1:\nThis study by Bakir et al. investigates the role of the early olfactory system in fear learning by\nexamining activity in olfactory sensory neurons (OSNs), mitral cells (MTs), and periglomerular\n(PG) cells within the olfactory bulb (OB). By manipulating GABA receptor activity through the\nuse of an antagonists and an agonist, the authors demonstrate that inhibitory processing in the\nearly olfactory pathway plays a critical role in fear learning and, potentially, early memory\nformation. This finding significantly extends previous work on sensory disinhibition—\nparticularly in the primary auditory cortex—by demonstrating a similar mechanism in early\nolfactory areas. The study is methodologically rigorous, and the results largely support the\nauthors' conclusions. However, I offer several suggestions for further strengthening the\nmanuscript:\n1. Conceptual framing: To broaden the theoretical context, the authors could integrate earlier\nwork on disinhibition in the auditory cortex. Specifically, the following studies may be useful in\nanchoring the current findings within a broader framework for associative fear learning and\nmemory:\no Letzkus, J. J., Wolff, S. B., & Lüthi, A. (2015). Disinhibition, a circuit mechanism for\nassociative learning and memory. Neuron, 88(2), 264–276.\no Letzkus, J. J., Wolff, S. B., Meyer, E. M., et al. (2011). A disinhibitory microcircuit for\nassociative fear learning in the auditory cortex. Nature, 480(7377), 331–335.\nWe thank the reviewer for their kind words about our methodological rigor and the strength of\nour conclusions. We also appreciate their thoughtful synthesis of our findings within the broader\nliterature on sensory disinhibition and associative learning. We now discuss disinhibition of local\ncircuitry during learning as a recurring circuit motif in the Introduction, including direct\nreference to the auditory cortex as suggested (page 2, paragraph 5). We have also added a full\nparagraph to the discussion exploring the similarity of our findings to those reported in the\nauditory system (page 13, paragraph 3).\n2. Result interpretation: The pharmacological manipulation in the olfactory bulb affects multiple\ncell types (OSNs, PG cells, and MT cells), making it difficult to isolate the causal role of OSNs in\nfear learning. While the title appropriately avoids specifying OSNs, the Introduction places\nalmost exclusive emphasis on them, and the Discussion does not sufficiently explore alternative\nexplanations involving PG or MT cell contributions. A more balanced consideration of these\npossibilities would strengthen the overall interpretation.\nWe of course agree that pharmacological manipulation of GABA receptors in the olfactory bulb\nB\naffects multiple cell types and we thank the reviewer for bringing this oversight to our attention.\nWe have added a sentence to the Introduction to establish this possibility up front (page 2,\nparagraph 4) and a full paragraph to the Discussion (page 13, paragraph 2) to explicitly consider\nour data in light of these broader effects on the circuit.\n3. Fear generalization: While the generalization gradient observed is compelling, the data do\nnot conclusively rule out the alternative interpretation that disinhibition directly influences fear\nlearning and only secondarily affects generalization. This distinction could be more clearly\naddressed in the discussion.\nThe pharmacological manipulations reported here were performed only after conditioning had\nalready occurred, but the reviewer is correct that the interpretation of the behavioral\ngeneralization we observed could differ depending on one’s underlying conceptual understanding\nof generalization itself. We have added a full paragraph to the discussion exploring the disparate\npossibilities of generalization linked to stimulus confusion, generalization linked to gradient\nbroadening, and generalization linked to gradient elevation (page 12, paragraph 2) and\nsuggesting potential means of disentangling these possibilities.\n4. Figure presentation (minor point): Some figure captions would benefit from additional\nexplanation to help readers interpret the results more effectively without referring back to the\nmain text.\nWe thank the reviewer for this suggestion and have revised the figure captions throughout the\nmanuscript to provide additional explanatory detail, clarify experimental context, and improve\nstand-alone interpretability without requiring reference to the main text.\nReviewer #2:\nBakir et al. investigated the neural mechanism underlying fear generalization using an odor\n(CS+)-mediated, contextual fear conditioning paradigm in mice. The authors show that odor\nfear conditioning induced fear responses (immobility) and odor avoidance in an open field\narena, which can be generalized to other odors based on their similarity to the CS+ odor. This\ngeneralization is linked to overlapping and spatial proximity within the olfactory bulb activation\nmap. The authors further show that fear generalization is regulated by GABAB receptor\nsignaling in the olfactory bulb via pharmacological manipulations. Blocking GABAB receptors\nwith an antagonist in fear-conditioned mice leads to broader fear generalization to other odors,\nwhile infusion of a GABAB agonist shows reduced fear generalization. The authors demonstrate\nthat downregulation of GABAB receptor-mediated inhibition enhances fear generalization via\nrepresentational plasticity rather than sensory confusion. The overlap and spatial relationship\nbetween glomerular responses to different odors underpin the spread of fear. Given the\nconserved role of GABAB signaling across sensory systems, these results suggest a broader\nrelevance for understanding mechanisms underlying generalized anxiety disorders. The study is\nwell-designed with appropriate controls and statistical analyses and is clearly written. The\nmanuscript would be further improved if the following concerns were addressed.\nWe thank the reviewer for their praise of our experimental design and sincerely appreciate their\nsuggestions, which we have incorporated throughout.\nMajor:\n1. Activation of GABAB receptors in the olfactory bulb with baclofen is expected to reduce\nglutamate release from OSNs. Therefore, baclofen-induced behavioral effects shown in Fig. 4\ncould be potentially due to altered odor detection/discrimination, but not failed fear\ngeneralization to other odors. Olfactory bulb imaging experiments (parallel to those shown in\nFig. 2B-I for the GABAB antagonist) and/or behavioral tests to show that mice can still\ndistinguish the three odors would help to rule out this possibility and further strengthen the\nconclusions.\nThe reviewer makes an excellent point, and we have performed an additional behavioral\nexperiment (new Fig. 5) to address this concern. We used an identical infusion of baclofen into\nthe olfactory bulbs of mice prior to passive presentations of the three study odorants using a\nwithin-subjects habituation/dishabituation paradigm (Methods: page 16, paragraph 2 and Results:\npage 11, paragraph 4). Baclofen did not impair odor discrimination at all: mice that received\nbaclofen infusions exhibited normal habituation to repeated odor presentations and robust\ndishabituation upon odor change, with no significant main effect of drug vs vehicle control or\ndrug-by-trial interaction during odor switches. This confirms that these mice could detect and\ndiscriminate these odors and supports the interpretation that its effects on behavior reflect\nmodulation of fear generalization rather than sensory confusion. We believe these data are\nsufficient to address the reviewer’s concern. We have not added physiological experiments with\nbaclofen because a) physiological effects of baclofen on this circuit have been reported dozens of\ntimes previously by ourselves and others in multiple labs and species (e.g. Wachowiak et al.\n2005; McGann et al. 2005), and b) the effects of exogenous agonists are much harder to interpret\nthan the effects of antagonists blocking naturally occurring signaling.\nJ. P. McGann et al., Odorant representations are modulated by intra- but not interglomerular\npresynaptic inhibition of olfactory sensory neurons. Neuron 48, 1039-1053 (2005).\nM. Wachowiak et al., Inhibition of olfactory receptor neuron input to olfactory bulb glomeruli\nmediated by suppression of presynaptic calcium influx. Journal of neurophysiology 94, 2700-\n2712 (2005).\n2. In addition to the OSN axon terminals, GABAB receptors are also expressed in other cell types\nin the olfactory bulb. The authors should discuss potential contributions from other cell types to\nfear generalization after exogenous application of GABAB agonists and antagonists.\nWe thank the reviewer for bringing this oversight to our attention and have added text to both the\nIntroduction and Discussion as described in the response to Reviewer 1.\nMinor:\n1. Both male and female mice are used in the study. Is there a sex difference observed in the\nmouse behavior? It would be helpful to use different symbols for male and female mice in Fig.\n1C. For example, use x for males and circles for females.\nWe thank the reviewer for reminding us to include these analyses where possible. We did not\nobserve any sex differences in the pre-imaging behavioral experiments. We have updated Fig. 1c\nto use different symbols for male and female mice and added the corresponding statistical\ninformation to the figure caption. The optical neurophysiology data from these mice similarly\nshowed no detectable sex differences, F = 0.22, p = 0.80, η2 = 0.006. For the highly\n2,63\nmultivariate open-field avoidance experiments, our sample sizes were insufficient to support post\nhoc analyses of potential sex differences, so these are not reported in accordance with the\njournal’s guidelines for consideration of sex as a biological variable.\n2. In all figure legends, the animal numbers and trial numbers should be provided wherever\napplicable.\nThese numbers have been added throughout.\n3. In reporting one-way ANOVA results, n2 or η² is used in different places to represent eta-\nsquared. Please make it consistent throughout.\nThank you for pointing out this typographical error. We have corrected the manuscript to report\neta-squared consistently as η² for all one-way ANOVA results.\n4. In Figure 2 or Figure 3, it would be helpful to show examples of ROIs. This will help readers\nto appreciate how much overlap there is across the activation patterns induced by different\nodors.\nWe have revised Fig. 3a to include representative examples of odor-responsive ROIs, showing\nthe top five maximally responding ROIs for each odor and marking examples of jointly\nresponsive glomeruli with arrows, to better illustrate overlap across odor-evoked activation\npatterns.\n5. In Fig. 2C, suggest using “OSN Somas” instead of “OSN Bodies”.\nWe have revised the label in Fig. 2c to read “Somas.”\n6. In Fig. 2B, in the label “BEHAVIOR CONTROL (CS+)”, there is no CS+ odor in the control\ngroups. Suggest removing “CS+” but using MV (the odor name instead). Please define RLI in\nthe figure legend.\nWe have revised the label in Fig. 2B to remove “CS+” and instead use the odor name (MV), and\nwe have added a definition of RLI to the figure legend.\n7. Page 5. Last sentence. “odor-evoked responding”, suggest changing to “odor-evoked\nresponse”.\nWe have corrected this phrasing.\n8. Description of Fig. 3A legend seems inaccurate. It states “…across the dorsal bulb for MV\n(2nd row) are closer to BA (3rd row) than to HEX (bottom)”, while all three images are in the\nsame row.\nWe are especially grateful to the reviewer for pointing out this typographical error. We have put\nnumbers on the images and referred to these numbers in the captions instead.\n9. Page 11. “…OSN inputs to the bub”, where “bub” should be “bulb”.\n10. On page 7, “… the effect of overlapping glomeruli resembled the effect in OSNs (Fig. 2D,\n...”. It should be Fig. 3D instead of Fig. 2D.\n11. In Fig. 4E legend, “with color scale bar a right” should be “…at right”.\nWe have corrected these typographical errors.\nReviewer #3:\nI co-reviewed this manuscript with one of the reviewers who provided the listed reports. This is\npart of the Nature Communications initiative to facilitate training in peer review and to provide\nappropriate recognition for Early Career Researchers who co-review manuscripts.\nWe thank the reviewer for their contributions to our manuscript and hope that the experience was\na positive one."}, {"round": 2, "reviewer_comments": {"reviewer_1": "The authors have adequately addressed my concerns.", "reviewer_2": "The authors have satisfactorily addressed the critiques raised in the initial review. We have no further comments.", "reviewer_3": "I co-reviewed this manuscript with one of the reviewers who provided the listed reports. This is part of the Nature\nCommunications initiative to facilitate training in peer review and to provide appropriate recognition for Early Career\nResearchers who co-review manuscripts."}, "author_response": ""}]

Decision letter