Abstract
There is a strong association between traumatic brain injuries (TBIs) and the development of psychiatric disorders, including post-traumatic stress disorder (PTSD). Exposure-based therapy is a first-line intervention for individuals who suffer from PTSD and other anxiety-related disorders; however, up to 50% of individuals with PTSD do not respond well to this approach. Fear extinction, a core mechanism underlying exposure-based therapy, is a procedure in which a repeated presentation of a conditioned stimulus in the absence of an unconditioned stimulus leads to a decrease in fear expression, and is a useful tool to better understand exposure-based therapy. Identifying predictors of extinction would be useful in developing alternative treatments for the non-responders. We recently found that CO2 reactivity predicts extinction phenotypes in rats, likely through the activation of orexin receptors in the lateral hypothalamus. While studies have reported mixed results in extinction of fear after TBI, none have examined the long-term durability of this phenotype in the more chronically injured brain. Here we tested the hypothesis that TBI results in a long-term deficit in fear extinction, and that CO2 reactivity would be predictive of this extinction phenotype. Isoflurane-anesthetized adult male rats received TBI (n = 59) (produced by a controlled cortical impactor) or sham surgery (n = 29). One month post-injury or sham surgery, rats underwent a CO2 or air challenge, followed by fear conditioning, extinction, and fear expression testing. TBI rats exposed to CO2 (TBI-CO2) showed no difference during extinction or fear expression relative to shams exposed to CO2 (sham-CO2). However, TBI-CO2 rats, showed significantly better fear expression than TBI rats exposed to air (TBI-air). In contrast to previous findings, we observed no relationship between CO2 reactivity and post-extinction fear expression in either the sham or TBI rats. However, compared to the previously observed naïve sample, we observed more variability in post-extinction fear expression but a very similar distribution of CO2 reactivity in the current sample. Isoflurane anesthesia may lead to interoceptive threat habituation, possibly via action on orexin receptors in the lateral hypothalamus, and may interact with CO2 exposure, resulting in enhanced extinction. Future work will directly test this possibility.
1. Introduction
According to recent data from the Centers for Disease Control and Prevention (CDC), there were approximately 223,135 traumatic brain injury (TBI)-related hospitalizations and 64,362 deaths in 2019 alone (). Males were twice as likely as females to be hospitalized, with three times the risk of mortality, spanning early life to the aged population (). TBIs are well-known for their heterogeneity (), which is, in part, attributed to the variable nature and severity of the insult and brain regions involved. Regardless of this heterogeneity, there is a strong association between TBIs and the subsequent development of psychiatric disorders, including altered mood, psychoses, anxiety, stress, depression, substance abuse and posttraumatic stress disorders (PTSD) (Whelan-Goodinson et al., 2009; ; ; ; ). PTSD frequently presents as a comorbid condition among brain-injured patients (); however, several factors likely influence their association, including a history of mental illness prior to a TBI, gender, level of education, severity and type of injury, and time post-injury (Whelan-Goodinson et al., 2010; ; ).
Traumatic brain injury (TBI)-related PTSD has been extensively studied in the military population (Vasterling et al., 2018). As a signature of the conflicts in Iraq and Afghanistan (), 43.9% of brain-injured soldiers who experienced loss of consciousness met criteria for a PTSD diagnosis (). reported that 26% of troops, returning from Iraq with a diagnosed mild TBI, screened positive for PTSD, compared to 7% without a brain injury (; Wojcik et al., 2010). Furthermore, a meta-analysis of military and civilian populations found military personnel are nearly 3 times more likely to develop PTSD following a TBI than civilians (). The target population for these analysis are mostly male dominated as they are, in general, 40% more likely to experience a TBI () and are more prominent in the military population.
Trauma-focused therapy such as prolonged exposure therapy (PE) and cognitive processing therapy (CPT) are first-line interventions for individuals who suffer from PTSD (). However, meta-analyses of randomized-controlled trials (RCTs) () and practice-based studies () suggest that non-responder rates may be as high as 50%. Fear extinction, a procedure in which the repeated presentation of a conditioned stimulus in the absence of the unconditioned stimulus leads to a decrease in fear expression, is a core mechanism underlying exposure-based therapy, and evidence suggests that PTSD is associated with extinction deficits ().
Studies have used fear conditioning to examine the impact of TBIs on fear learning in rodents, but far fewer have assessed the effects of TBIs on extinction (; ; Sierra-Mercado et al., 2015; ; ; ; ; ; Zhao et al., 2021). Within the subset of studies that did examine extinction post-injury, there is variability in outcomes, ranging from no difference in extinction (Sierra-Mercado et al., 2015), to impaired extinction (Zhao et al., 2018) or a resurgence in fear after extinction learning (). There have also been reports of both an increase (; ; ) or decrease in freezing during fear acquisition following injury (; ; ; ; see Table 1). The lack of consistency in these findings is likely due to several factors including the nature of the brain injury (focal versus diffuse), variations in fear conditioning, extinction, or both, as well as the timepoint after injury at which extinction is assessed. Because TBIs may elicit progressive neurodegeneration throughout the neuroaxis (), the emergence of extinction deficits (and possibly PTSD) may be critically linked to time post-injury.
TABLE 1
| References | Species | TBI model | % isoflurane | Anesthesia | DPI | Cued | Context | Ext learning | Fear expression | Fear resurgence |
| Rats N = 16–19/group | LFP | 2–1% | 1× | FC: 2 DPI | Pure tone: Freezing after TBIWhite noise: no difference | Pure tone: no difference White noise: Freezing after TBI | White noise context: Freezing after TBI | White noise context: Freezing after TBI | N/A | |
| Zhao et al., 2018 | Rats N = 8/group | LFP | 5–2.5% | 1× | FC: 28 DPI | N/A | No difference | Freezing after TBI | Freezing after TBI | N/A |
| Rats N = 10/group | WD | 4–3% | 1× | FC: 8 DPI | N/A | Freezing after TBI | No difference | No difference | N/A | |
| Sierra-Mercado et al., 2015 | Mice N = 6–12/group | CCI | 4–3% | 1× | FC: 14 DPI | No difference | No difference | No difference | No difference | N/A |
| Mice N = 10–15/group | CCI | 3–1% | 1× | FC: 21 DPI Ext. Resurgence: 42 DPI | Freezing after TBI | N/A | No difference | No difference | Freezing after TBI | |
| Mice N = 6–11/group | CCI | 5–2.5% | 1× | FC: 14 DPI | N/A | Freezing after TBI | Freezing after TBI | Freezing after TBI | N/A | |
| Mice N = 6–11/group | Single and repetitive blast (4×) | 3% | 1×–4× | FC: 3 DPI 7 DPI 56 DPI | Freezing after TBI (1× and 4×) for trace conditioning at 3 days and 1 week, but not 8 weeks after TBI | No difference | No difference | N/A | N/A | |
| Rats N = 10/group | Repetitive blast (3×) | 5% isoflurane | 3× | FC: −1 DPI Ext: 4 DPI–56 DPI | Freezing after TBI | N/A | No difference | No difference | No difference | |
| Rats N = 11–12 per group | WD + Stressor | 4–3% isoflurane | 1× | FC: 7 DPI | N/A | No difference | Freezing after TBI, stressed rats and combined treatments | Freezing in only combined treatments | N/A |
Brain-injured rodents show alterations in fear acquisition and extinction.
Summary of fear conditioning and extinction in diffuse and focal models of TBI. LFP, lateral fluid percussion; CCI, controlled cortical impact; WD, weight drop; FC, fear conditioning; Ext, extinction,
= increased,
= decreased; N/A, not applicable; DPI, days post-injury; LTM, long- term memory.
Although results vary as to the effect of TBI on extinction, there are substantial individual differences in the response to extinction, even among healthy subjects (; Shumake et al., 2014, 2018). Identifying predictors of extinction would be useful in developing alternative treatments for the non-responders. There is evidence to suggest that individual differences in extinction phenotype are, in part, due to increased orexin neuronal activity in the hypothalamus (; ). Interestingly, these same orexin neurons are activated in the presence of CO2 inhalation (). Indeed, found that CO2 reactivity predicts extinction phenotypes in rats, likely through the activation of orexin receptors in the lateral hypothalamus. Since CO2-exposure is associated with increased activity of orexin neurons in the lateral hypothalamus (), reactivity to elevated CO2 levels may serve as prognostic marker for poor extinction learning. Similarly, those with anxiety disorders display heightened emotional reactivity to a single inhalation of 35% CO2 (Telch et al., 2010). In soldiers, CO2 reactivity pre-deployment predicted the emergence of PTSD and symptoms of anxiety (but not depression) while deployed in Iraq (Telch et al., 2012). Individuals with PTSD show extinction deficits (), reinforcing the potential for CO2 reactivity to be a good predictor of extinction phenotypes.
In the present study, we examined brain-injured rats beginning 1 month post-injury (N = ∼29/group), a time point at which extinction deficits become evident in rats that received a TBI (Zhao et al., 2018; ). We hypothesized that TBI would result in a disruption in extinction, and that CO2 reactivity would predict variability in extinction phenotypes.
2. Materials and methods
2.1. Animals
Adult male Sprague-Dawley rats 60–70 days old (n = 88, 300–350 g, Charles River, Raleigh, NC, USA) were tri-housed in transparent polyethylene cages (27 cm × 48 cm × 20 cm) and provided with ad libitum food and water. Housing was temperature and humidity-controlled (70°F, 44% humidity) with a 12 h/12 h light/dark cycle. All procedures were approved by the University of Texas at Austin Institutional Animal Care and Use Committee. They were also in accordance with the National Institutes of Health Guide for the Care and Use of Laboratory Animals.
2.2. Experiential timeline
Rats (n = 88) underwent either a TBI or sham surgery. At 1 month post-injury (PI), animals that received TBIs were screened for reactivity to CO2 (TBI-CO2) (n = 30) or normoxic air (TBI-air) (n = 29), while all sham animals (n = 29) were screened for CO2 reactivity (sham-CO2). Then 6 days later, all groups of rats were fear conditioned using 3 tone shock (US) pairings with conditioned stimulus (CS). The next day, they received an extinction session (19 CSs without US). The day after extinction, rats were tested for fear expression using 4 CSs without US. Either 3 or 4 days later, all animals received a CO2 challenge and were sacrificed 1 h later. Brains were removed and prepared for immunohistochemistry (see Figure 1).
FIGURE 1
2.3. Controlled cortical impact
Each rat received a focal brain injury (TBI), produced by a controlled cortical impactor (CCI), as previously described (; ). Briefly, the rat was anesthetized in a 4% isoflurane chamber and then positioned in a stereotaxic frame with an anesthetic mask delivering 2.5% isoflurane throughout the surgery. A midline incision was made to expose the skull followed by a circular craniectomy midway between bregma and lambda. Each animal was randomly assigned to receive either a TBI (n = 59) or sham surgery (n = 29). Injury parameters were set at 4.0 m/s velocity and a 2.0 mm depth of penetration using a 6.0 mm convex impactor tip. Sham surgery consisted of the same surgical procedures, including craniectomy, but without CCI. All rats received bupivacaine (0.25%, < 8 mg/kg, subcutaneous) locally at the incision site before craniectomy and buprenorphine (0.05 mg/kg, subcutaneous) immediately following surgery and again 6–8 h later.
2.4. Screening for CO2 reactivity
Gas was delivered through a custom built plexi-glass flow chamber (12″ width × 12″ height × 24″ length). Flow was controlled using a two-stage regulator (Praxair, Inc., Danbury, CT, USA) that delivered gas to the chamber. Ambient air entered the chamber for the first 30 s after the rat was introduced to the chamber. This was followed by a 2 min induction phase, during which 25% CO2 was infused into the chamber causing the CO2 percentage to slowly rise. CO2 was held at 25% for an additional 2 min, after which the chamber was flushed with atmospheric air allowing the CO2 percentage to return to normal levels. After 4 min of flushing with atmospheric air, the rat was transferred to its home cage (Figure 2).
FIGURE 2
2.5. CO2 behavioral analyses
The scoring system for CO2 reactivity was adapted from . Briefly, each behavior was quantified at baseline (30 s), during CO2 induction (2 min), hold period (2 min) and during flush-out period (4 min). Behaviors were monitored through a video camera and were hand scored by an observer, blinded to the experimental condition. The following behaviors were quantified: ambulation (A), grooming (G), rearing (R), and labored breathing (L). For coding purposes, induction was referred to as phase 1, 25% hold phase 2, and the first and second half of flush-out as phases 3 and 4.
2.6. CO2 challenge and brain collection
At the end of the experiment, all rats received a CO2 challenge (as previously described above under CO2 screening). One hour post CO2 challenge, rats received a lethal dose of Euthasol (Vibric, 1 ml/200 g) and were intracardially perfused with phosphate buffered saline followed by 4% paraformaldehyde (PFA). The brains were extracted and stored in 4% PFA overnight, then transferred into 30% sucrose solution.
2.7. Apparatus
All experimental manipulations (fear conditioning, extinction, fear expression) were administered in the same context (operant conditioning chambers; Coulbourn Instruments, Whitehall, PA, USA). Chambers were equipped with stainless-steel rod floor bottoms connected to a shock generator (Model H10-11R-TC-SF; Coulbourn Instruments). All chambers were illuminated under red light. Behavior was recorded by infrared digital cameras (Panasonic, model wvBP344, Osaka, Japan), mounted on the ceiling of each unit. An automated stimulus presentation was elicited using Freezeframe2 software (Coulbourn Instruments, Whitehall, PA, USA). Between each session, chambers were cleaned with Windex (SC Johnson, Racine, WI, USA).
2.8. Fear conditioning
Rats were placed in the conditioning chambers for a 3 min habituation period followed by fear conditioning with three 20 s 5 kHz, 80 dB tones conditioned stimulus (CS). Each CS was co-terminated with a 500 ms, 0.7 mA footshock (US). The interval between each CS was on average 120 s in duration. After conditioning, rats remained in the chamber for 3 min and then were returned to the home cage.
2.9. Extinction
The day after conditioning, subjects were returned to the same conditioning chambers where they reacclimated for 3 min. This was followed by 19 CS presentations without the US, with variable intervals with a mean of 180 s. After the extinction trial, animals remained in the chamber for 3 min before returning to the homecage.
2.10. Fear expression test
The day after extinction, rats were returned to the conditioning chamber, acclimated for 3 min, then presented with 4 CSs without US. The interval between each CS was on average, 120 s in duration. Rats reminded in the chamber for 3 min before returning to the homecage.
2.11. Behavioral scoring: freezing
Freezing was defined as the absence of movement aside from breathing, scanning and ear twitching, and excluded sleeping or resting. All behaviors were scored manually by an individual who was blinded to the experimental conditions.
2.12. Quantification of lesion volume
Lesion volume, determined at 1 month post-injury, was based upon 40 μm coronal sections stained with hematoxylin and eosin. Measurements of the cortical mantel were taken from both the contralateral and ipsilateral hemispheres using a Nikon Ni-E microscope (Nikon Instruments Inc., NY, USA) spanning Bregma 1.5 to −3.8 mm. This yielded 8–10 sections per brain, using a sampling interval of 12, a 2× objective and a grid size of 400 μm. Cortical measurements were performed by an individual who was blinded to the experimental conditions. Cortical volume was estimated as the product of summed areas of sections and the distance between sections. Lesion volume was then calculated as the difference between volumes of the contralateral and ipsilateral cortices (Tennant et al., 2015; ).
2.13. Statistical analyses
R (, Vienna, Austria), together with the packages beset (Shumake et al., 2018) and nlme (), were used to perform all statistical analyses. Fear acquisition, extinction and fear expression were compared between TBI-CO2 and TBI-air rats as well as TBI-CO2 and sham-CO2 groups using a repeated measures ANOVA, this data included the pre-CS. Data is expressed as mean ± standard error. Exclusion from analysis occurred if video footage was not captured completely (n = 7 Extinction).
A modified version of the “best subset” approach to linear regression was used to determine which of the CO2-reactivity behaviors accounted for the greatest portion of variance in post-extinction fear expression, the first 2 CS of fear expression, freezing. This approach fits a different linear model for every possible combination of predictor variables. We then used resampling (k-fold cross validation where k = 10) to estimate how well each model would predict new samples in terms of mean squared error (MSE). Each model was repeatedly refitted to random subsamples of data and then tested for how well it predicted the remainder of the data. The “best” model was then chosen as the one with the fewest predictors and was within one standard error of the model with the smallest MSE, i.e., the best at predicting new data. Nested cross-validation was used to avoid overly optimistic estimates of prediction error when selecting the best model.
3. Results
3.1. No differential effects between TBI and sham groups that received CO2
Rats received either a TBI (TBI-CO2) or sham (sham-CO2) surgery followed by a brief exposure to CO2 (n = 30) or a TBI (TBI-air) with an exposure to normoxic air (n = 29), one-month post-surgery, followed by fear conditioning, extinction and fear expression. TBI-air rats served as a control group to ensure there were no interacting effects of surgery and CO2 on behavior. We compared groups over the course of fear acquisition, extinction and fear expression (Figure 3). Our primary hypothesis was that TBI would result in a disruption in extinction. We first determined if there was an effect of TBI alone on the measured behaviors. We found no significant differences between TBI-CO2 and sham-CO2 groups during extinction [F(1, 51) = 0.22, p = 0.637] or fear expression [F(1, 57) = 0.114, p = 0.736]. However, a significant interaction was found between groups during fear acquisition [F(2, 114) = 6.82, p = 0.001] with a main effect between groups [F(1, 57) = 5.30, p = 0.02]. This difference seen in fear acquisition is driven by the 2nd conditioned stimulus (CS2) alone and did not persist throughout the remainder of fear conditioning nor did this difference hold up at the beginning of extinction.
FIGURE 3
3.2. Within TBI groups, CO2 exposure results in a decreased freezing 24 h post-extinction
A control group was used to ensure there were no interacting effects of TBI surgery and CO2 on preceding behaviors (TBI-air). We compared both groups, TBI-CO2 and TBI-air, throughout fear acquisition, extinction and fear expression (Figure 4). There was no significant difference between TBI-CO2 and TBI-air groups during both fear acquisition [F(1, 57) = 2.20, p = 0.14] and extinction [F(1, 52) = 1.22, p = 0.27]. However, TBI-CO2 rats showed a decrease in freezing during fear expression compared to TBI-air group [F(1, 57) = 4.01, p = 0.05].
FIGURE 4
3.3. CO2 reactivity does not predict post-extinction fear expression in rats receiving TBI or sham surgery
We previously showed that CO2 reactivity was predictive of post-extinction fear expression behavior in naïve rats (). Here we tested whether CO2 reactivity can predict post-extinction fear expression in injured and sham rats. Post-extinction fear expression was defined as the mean freezing of the first two trials of fear expression. In order to determine if CO2 reactivity was a good predictor of post-extinction fear expression, we first ran a regression analysis using the previous a priori predictor separately (A3) for the TBI-CO2 and sham-CO2 groups together and separately. In , A3 (ambulation during the flush-out phase) had a cross-validation R2 estimate of 0.085 meaning it was assessed to be reliably good at predicting 8.5% of fear expression variance. Thus, we considered this an a priori predictor. When combining TBI-CO2 and sham-CO2 rats, A3 did not predict post-extinction fear expression (t = 0.076, p = 0.939). TBI (t = 0.909, p = 0.372) and sham groups (t = −0.609, p = 0.547) alone also showed A3 was also not a significant predictor for post-extinction fear expression. Overall, A3 alone was not a significant predictor of post-extinction fear expression.
In order to examine all of the behaviors measured during the CO2 challenge, we analyzed each group (TBI-CO2 and sham-CO2) separately and together with the best-subset approach. With these parameters, the TBI-CO2 and sham-CO2 group combined, the null (intercept-only) model was the best model selected for 97% of random subsamples. In the sham-CO2 group alone, the best model was also a null model. So, when examining the two groups combined or the sham-CO2 group alone, CO2 reactivity did not predict post-extinction fear expression.
This same approach was then used for the TBI-CO2 group to determine the best predictive effect of CO2 reactivity. The null model was selected 50% of the time. Labored breathing during flush-out-1 (L3) also was selected about 30% of the time, and explained 9.3% of the variance in the full sample, but this fell to approximately 0% of the variance in the hold-out samples. Therefore, it seems likely that this predictor is detecting something that is sample specific and is not likely to replicate.
3.4. No difference in lesion volume between groups that received a TBI
Brain injured animals were randomly assigned to 2 groups; namely, those screened for reactivity to CO2 (TBI-CO2) or normoxic air (TBI-air). Due to differences in freezing behavior, we compared lesion volumes in each of these groups (Figure 5). As this was not part of the original hypothesis, we only chose a subset of each group that upon evaluation had no artifact from brain removal or mounting. There were no significant differences in lesion volume between the group that received CO2 and the control group [t(9) = 0.88, p = 0.39].
FIGURE 5
3.5. Exploratory analyses
Since this study did not replicate our previous findings, which showed that CO2 was a good predictor of post-extinction fear expression in naive rats (), we next examined what may have been different between the 2 populations. Our aim was to use the naive rats from our 2019 study to compare the distribution of CO2 reactivity and freezing during post-extinction fear expression, and the CO2 curves between studies.
3.5.1. Shifted distribution in post-extinction fear expression and A3 compared to original naive sample
Using previous data from , we compared the original data distributions of the a priori predictor (A3) and post-extinction fear expression to the new distributions of sham-CO2 rats. In order for a predictive model to successfully generalize from one sample to another, a minimum requirement would be no large shifts in the observed distributions of either the covariates or the response variables. The observed measurements in this study failed to meet this basic assumption. Compared to the naïve rats in the previous study, post-extinction fear expression freezing was far more variable (SD = 32.0 vs. 14.8) and skewed more toward 0 (M = 33.1 vs. 50.7), while the measurement of A3 ambulation was skewed toward higher values (Figure 6).
FIGURE 6
3.5.2. CO2 reactivity is greater in current study during intro and flush out phases
We then compared the distributions of CO2 reactivity between TBI-CO2 and sham-CO2 groups, along with the naive sample previously found in
FIGURE 7

The comparison of measured CO2 reactivity between TBI-CO2, sham-CO2 and naive groups (from
FIGURE 8

The comparison of measured CO2 reactivity between TBI-CO2, sham-CO2 at euthanasia. The TBI-CO2 and sham-CO2 group both have very similar distributions for all of the behaviors measured.
3.5.3. Compared to the original CO2 curve, the induction of CO2 is greater and the speed of flush out is slower
The CO2 challenge in this study was meant to replicate that seen in
FIGURE 9

(A)
4. Discussion
This study examined the effects of TBI on the extinction of fear and determined if CO2 reactivity is a predictor of extinction variability following TBI. Contrary to our a priori hypothesis, we found that TBI alone did not have an effect on extinction, but rather the combination of CO2 and prior TBI resulted in a decrease in freezing behavior during post-extinction fear expression. We did see a significant decrease in freezing during fear conditioning in TBI rats compared to sham. CO2 reactivity did not predict variability seen in post-extinction fear expression in sham or TBI rats. These findings are at odds with our prior hypothesis, but in the context of previous literature, these results have validity.
There are a number of preclinical models of TBI that generate focal and diffuse injuries and are characterized by temporal patterns of neurodegeneration that reflect the type of injury, magnitude, and location of the initial insult (Xiong et al., 2013). As such, it is often difficult to compare behavioral findings across studies where there is inherent variability in behavioral protocols, as well as differences in sample size, the preclinical models employed including when the assays are conducted post-injury. Despite these differences, a few patterns can be extracted from the relevant studies (see Table 1). For example, studies that utilized delayed timepoints (15–28 days) reported extinction deficits in rodents after using either a lateral fluid percussion insult (Zhao et al., 2018) that induces diffuse axonal injury or a CCI (
Previous studies that have examined the effect of TBI on fear acquisition and extinction have all employed somewhat different protocols. Our approach was in line with that used in
The mechanisms that underlie fear conditioning and extinction are well established and are dependent on brain regions that are compromised in individuals suffering from TBI and PTSD. Alterations in the amygdala, hippocampus, thalamus and prefrontal cortext (PFC) result in moderation of fear conditioning and extinction (
There is strong evidence that that CO2 reactivity may serve as a diagnostic tool in predicting the emergence of fear related disorders. In humans, anxiety disorders display heightened reactivity to a single inhalation of 35% CO2 (Telch et al., 2010;
Indeed, the underlying mechanisms, hypothesized to explain the relationship between CO2 and extinction, are known to be affected by isoflurane exposure. Exposure to CO2 activates orexin neurons in the lateral hypothalamus (
In summary, this study is the first to utilize a chronic, focal model of TBI to examine CO2 as a diagnostic tool to explain variability in extinction in the degenerating neuroaxis in male rats. However, the interacting effects of prior TBI surgery, including isoflurane exposure, and CO2 have made it difficult to reach definitive conclusions regarding the impacts of TBI on the predictive relationship between CO2 reactivity and fear extinction. Recognizing the limitation of studying male rats only, future work should consider comparative studies of both sexes to determine if this interaction between CO2 and isoflurane may yield similar interoceptive threat habituation, resulting in better extinction when exposed to both inhalants.
Statements
Data availability statement
The datasets presented in this study can be found in online repositories. All raw data files are available in the Monfils Lab repository, housed in the Texas Data Repository in Dataverse https://dataverse.tdl.org/dataverse/monfilsfearmemorylab. Data is also publicly available at Open Data Commons for Traumatic Brain Injury (ODC-TBI) https://odc-tbi.org.
Ethics statement
The animal study was reviewed and approved by the University of Texas at Austin Institutional Animal Care and Use Committee and were in accordance with the National Institutes of Health Guide for the Care and Use of Laboratory Animals, and are in line with the ARRIVE guidelines.
Author contributions
MM, LN-H, and KS designed the study. KS carried out the study, SM, VR, MR, and MD provided technical assistance. JS provided statistical assistance. All authors contributed to the article and approved the submitted version.
Conflict of interest
The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
Publisher’s note
All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.
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Summary
Keywords
traumatic brain injury, CO2, fear conditioning, extinction, individual differences
Citation
Smith KA, Raskin MR, Donovan MH, Raghunath V, Mansoorshahi S, Telch MJ, Shumake J, Noble-Haeusslein LJ and Monfils MH (2023) Examining the long-term effects of traumatic brain injury on fear extinction in male rats. Front. Behav. Neurosci. 17:1206073. doi: 10.3389/fnbeh.2023.1206073
Received
14 April 2023
Accepted
26 May 2023
Published
16 June 2023
Volume
17 - 2023
Edited by
Seth Davin Norrholm, Wayne State University, United States
Reviewed by
Christopher Cain, Nathan Kline Institute for Psychiatric Research, United States; Craig Weiss, Northwestern University, United States; Christopher Olsen, Medical College of Wisconsin, United States; Jeff L. Weiner, Wake Forest University, United States; Shane Alan Perrine, Wayne State University, United States; Srini Kallakuri, Wayne State University, United States in collaboration with reviewer SP; Stefano Gaburro, Tecniplast, Italy
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Copyright
© 2023 Smith, Raskin, Donovan, Raghunath, Mansoorshahi, Telch, Shumake, Noble-Haeusslein and Monfils.
This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
*Correspondence: M. H. Monfils, Marie.monfils@utexas.edu
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