Understanding Individual Subject Differences through Large Behavioral Datasets: Analytical and Statistical Considerations.

A core feature of behavior analysis is the single-subject design, in which each subject serves as its own control. This approach is powerful for identifying manipulations that are causal to behavioral changes but often fails to account for individual differences, particularly when coupled with a small sample size. It is more common for other subfields of psychology to use larger-N approaches; however, these designs also often fail to account for the individual by focusing on aggregate-level data only. Moving forward, it is important to study individual differences to identify subgroups of the population that may respond differently to interventions and to improve the generalizability and reproducibility of behavioral science. We propose that large-N datasets should be used in behavior analysis to better understand individual subject variability. First, we describe how individual differences have been historically treated and then outline practical reasons to study individual subject variability. Then, we describe various methods for analyzing large-N datasets while accounting for the individual, including correlational analyses, machine learning, mixed-effects models, clustering, and simulation. We provide relevant examples of these techniques from published behavioral literature and from a publicly available dataset compiled from five different rat experiments, which illustrates both group-level effects and heterogeneity across individual subjects. We encourage other behavior analysts to make use of the substantial advancements in online data sharing to compile large-N datasets and use statistical approaches to explore individual differences.

Behavioral Interventions Can Improve Brain Injury-Induced Deficits in Behavioral Flexibility and Impulsivity Linked to Impaired Reward-Feedback Beta Oscillations.

Traumatic brain injury (TBI) affects a large population, resulting in severe cognitive impairments. Although cognitive rehabilitation is an accepted treatment for some deficits, studies in patients are limited in ability to probe physiological and behavioral mechanisms. Therefore, animal models are needed to optimize strategies. Frontal TBI in a rat model results in robust and replicable cognitive deficits, making this an ideal candidate for investigating various behavioral interventions. In this study, we report three distinct frontal TBI experiments assessing behavior well into the chronic post-injury period using male Long-Evans rats. First, we evaluated the impact of frontal injury on local field potentials recorded simultaneously from 12 brain regions during a probabilistic reversal learning (PbR) task. Next, a set of rats were tested on a similar PbR task or an impulsivity task (differential reinforcement of low-rate behavior [DRL]) and half received salient cues associated with reinforcement contingencies to encourage engagement in the target behavior. After intervention on the PbR task, brains were stained for markers of activity. On the DRL task, cue relevance was decoupled from outcomes to determine if beneficial effects persisted on impulsive behavior. TBI decreased the ability to detect reinforced outcomes; this was evident in task performance and reward-feedback signals occurring at beta frequencies in lateral orbitofrontal cortex (OFC) and associated frontostriatal regions. The behavioral intervention improved flexibility and increased OFC activity. Intervention also reduced impulsivity, even after cues were decoupled, which was partially mediated by improvements in timing behavior. The current study established a platform to begin investigating cognitive rehabilitation in rats and identified a strong role for dysfunctional OFC signaling in probabilistic learning after frontal TBI.

Discriminative-stimulus effects of cannabidiol oil in Sprague-Dawley rats.

Cannabidiol (CBD) is one of the major centrally active phytocannabinoid components of cannabis, and has been approved by the FDA only for the treatment of seizures associated with three rare disorders. It has also been touted as a potential treatment for anxiety in place of more traditional treatments like benzodiazepines. Although there is some evidence of anxiolytic effects of CBD, its suitability as a substitute for benzodiazepines is unknown. This experiment was designed to assess the extent to which CBD shares interoceptive discriminative-stimulus properties with the anxiolytic drug chlordiazepoxide (CDP), a benzodiazepine. In the present experiment, a range of doses (0-1569 mg/kg) of over-the-counter CBD oil was administered (i.g.) in male Sprague-Dawley rats trained to discriminate 5.6 mg/kg CDP from saline. Due to the long time-course effects of CBD, generalization tests were conducted at 90 and 120 min post-CBD administration. The two highest doses of CBD tested (1064 and 1569 mg/kg) were found to partially substitute for 5.6 mg/kg CDP, with mean percent responding on the CDP-associated lever reaching above 20% at time 2 (120 min post-CBD administration), suggesting that high doses of the over-the-counter CBD oils used in this experiment share interoceptive discriminative-stimulus properties to some degree with CDP. These results are novel in comparison to existing research into stimulus effects of CBD, in which substitution for benzodiazepines has not previously been observed.

Statistical power and false positive rates for interdependent outcomes are strongly influenced by test type: Implications for behavioral neuroscience.

Statistical errors in preclinical science are a barrier to reproducibility and translation. For instance, linear models (e.g., ANOVA, linear regression) may be misapplied to data that violate assumptions. In behavioral neuroscience and psychopharmacology, linear models are frequently applied to interdependent or compositional data, which includes behavioral assessments where animals concurrently choose between chambers, objects, outcomes, or types of behavior (e.g., forced swim, novel object, place/social preference). The current study simulated behavioral data for a task with four interdependent choices (i.e., increased choice of a given outcome decreases others) using Monte Carlo methods. 16,000 datasets were simulated (1000 each of 4 effect sizes by 4 sample sizes) and statistical approaches evaluated for accuracy. Linear regression and linear mixed effects regression (LMER) with a single random intercept resulted in high false positives (>60%). Elevated false positives were attenuated in an LMER with random effects for all choice-levels and a binomial logistic mixed effects regression. However, these models were underpowered to reliably detect effects at common preclinical sample sizes. A Bayesian method using prior knowledge for control subjects increased power by up to 30%. These results were confirmed in a second simulation (8000 datasets). These data suggest that statistical analyses may often be misapplied in preclinical paradigms, with common linear methods increasing false positives, but potential alternatives lacking power. Ultimately, using informed priors may balance statistical requirements with ethical imperatives to minimize the number of animals used. These findings highlight the importance of considering statistical assumptions and limitations when designing research studies.

Acute gut microbiome changes after traumatic brain injury are associated with chronic deficits in decision-making and impulsivity in male rats.

The mechanisms underlying chronic psychiatric-like impairments after traumatic brain injury (TBI) are currently unknown. The goal of the present study was to assess the role of diet and the gut microbiome in psychiatric symptoms after TBI. Rats were randomly assigned to receive a high-fat diet (HFD) or calorie-matched low-fat diet (LFD). After 2 weeks of free access, rats began training on the rodent gambling task (RGT), a measure of risky decision-making and motor impulsivity. After training, rats received a bilateral frontal TBI or a sham procedure and continued postinjury testing for 10 weeks. Fecal samples were collected before injury and 3-, 30-, and 60 days postinjury to evaluate the gut microbiome. HFD altered the microbiome, but ultimately had low-magnitude effects on behavior and did not modify functional outcomes after TBI. Injury-induced functional deficits were far more robust; TBI substantially decreased optimal choice and increased suboptimal choice and motor impulsivity on the RGT. TBI also affected the microbiome, and a model comparison approach revealed that bacterial diversity measured 3 days postinjury was predictive of chronic psychiatric-like deficits on the RGT. A functional metagenomic analysis identified changes to dopamine and serotonin synthesis pathways as a potential candidate mechanism. Thus, the gut may be a potential acute treatment target for psychiatric symptoms after TBI, as well as a biomarker for injury and deficit severity. However, further research will be needed to confirm and extend these findings. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Acute and long-lasting effects of adolescent fluoxetine exposure on feeding behavior in Sprague-Dawley rats.

The antidepressant medication fluoxetine (FLX) is frequently prescribed for the management of mood-related illnesses in the adolescent population-yet its long-term neurobehavioral consequences are not understood. To investigate how juvenile FLX exposure influences feeding behavior in adulthood, we conducted two experiments. In Experiment 1, adolescent male and female Sprague-Dawley rats were administered with 20 mg/kg/day FLX (postnatal day [PND] 35-49) and exposed to a binge access paradigm in adulthood (PND72+) to evaluate potential alterations for sweetened-fat preference. No long-term FLX-induced differences in preference for sweetened fat versus chow, nor total caloric intake, were noted; however, females displayed higher preference for sweetened fat compared to males. In Experiment 2, PND35 male rats received FLX (PND35-49) and were exposed to chronic variable stress (CVS) in adulthood (PND74-88). During treatment, FLX decreased body weight and intake (meal size), but not total meal number. Also, no differences in meal pattern parameters were observed after FLX completion. Likewise, no differences in meal pattern parameters to a palatable diet (45% fat, 17% sucrose) presented from PND74 to PND88, even after CVS, were observed. Our findings indicate that juvenile FLX reduces body weight gain acutely via reduced meal size intake; however, no long-term changes in ad libitum feeding behavior or binge access to a palatable stimulus are evident.

Large-N Rat Data Enables Phenotyping of Risky Decision-Making: A Retrospective Analysis of Brain Injury on the Rodent Gambling Task.

Decision-making is substantially altered after brain injuries. Patients and rats with brain injury are more likely to make suboptimal, and sometimes risky choices. Such changes in decision-making may arise from alterations in how sensitive individuals are to outcomes. To assess this, we compiled and harmonized a large dataset from four studies of TBI, each of which evaluated behavior on the Rodent Gambling Task (RGT). We then determined whether the following were altered: (1) sensitivity to overall contingencies, (2) sensitivity to immediate outcomes, or (3) general choice phenotypes. Overall sensitivity was evaluated using the matching law, immediate sensitivity by looking at the probability of switching choices given a win or loss, and choice phenotypes by k-means clustering. We found significant reductions in sensitivity to the overall outcomes and a bias toward riskier alternatives in TBI rats. However, the substantial individual variability led to poor overall fits in matching analyses. We also found that TBI caused a significant reduction in the tendency to repeatedly choose a given option, but no difference in win- or loss-specific sensitivity. Finally, clustering revealed 5 distinct decision-making phenotypes and TBI reduced membership in the "optimal" type. The current findings support a hypothesis that TBI reduces sensitivity to contingencies. However, in the case of tasks such as the RGT, this is not a simple shift to indiscriminate or less discriminate responding. Rather, TBI rats are more likely to develop suboptimal preferences and frequently switch choices. Treatments will have to consider how this behavior might be corrected.

Choice-based assessments outperform traditional measures for chronic depressive-like behaviors in rats after brain injury.

Depression is the most common psychiatric comorbidity to be diagnosed following traumatic brain injury (TBI). In clinical populations, TBI-induced depression may be particularly difficult to treat due to both unique underlying causes and the propensity for treatment resistance. Preclinical assays are needed to characterize depressive-like behavior in models of TBI and evaluate treatments. In the current study, two traditionally-acute assays of depressive-like behaviors, the Forced Swim Task and Saccharin Preference, were extended longitudinally to evaluate chronic TBI-induced depressive-like behaviors in male rats. Two chronic measures of motivation, the Progressive Ratio (PR) task and Effort Discounting Task (EDT), were also tested. The PR measures motivation to exert effort, while the EDT parametrically evaluates choice between low- and high-effort requirements. The EDT was the only assay which captured chronic depressive-like behavior after TBI, albeit with a degree of recovery over time. We found that traditionally-acute measures (Forced Swim Task, Saccharin Preference), and even our other chronic measure (PR), failed to capture long-term deficits. We also challenged serotonin and dopamine systems (via fluoxetine and bupropion) to evaluate how TBI-induced changes to these systems might drive depressive-like behaviors. Although we found no effect of fluoxetine, high-dose bupropion differentially impaired TBI rats. These findings suggest that (1) TBI-induced depressive symptoms remain difficult to measure at the preclinical level, (2) treatment for TBI-induced depression requires further exploration, and (3) obstacles at the preclinical level may translate to treatment failure at the clinical level.

Alternate day fasting decreases preference for a calorically dense diet by increasing chow intake and altering meal pattern parameters.

Alternate day fasting (ADF) is an effective dietary strategy for weight loss in both humans and rats. However, fasting can elicit hyperphagia in rats, particularly upon access to a calorically dense, high-energy (HE) diet. To examine the effects of ADF on HE diet preference, male and female Sprague-Dawley rats were randomly assigned to receive either ad-libitum or alternate day access to both chow and HE food. Meal pattern analysis was conducted to provide a more detailed explanation of changes in HE preference. ADF rats had a decreased preference for the HE diet compared to controls. Both male and female ADF rats increased in overall intake of chow. However, for male ADF rats, the decrease in HE preference was driven by an increase in both size and number of chow meals; for females, it was driven only by an increase in number of chow meals. Meal size is controlled by both positive feedback (e.g., from the oral cavity) and negative feedback (e.g., from postoral inhibitory signals). Thus, for males, fasting appeared to increase orosensory stimulation and/or decrease sensitivity to inhibitory cues towards chow. For females, fasting appeared to decrease sensitivity to inhibitory cues towards chow. The decrease in HE preference observed in the current study may contribute to the effectiveness of ADF as a dietary strategy for weight loss.