Corticostriatal dynamics underlying components of binge-like consumption of palatable food in mice.

Binge eating (BE) is a maladaptive repetitive feeding behavior present across nearly all eating disorder diagnoses. Despite the substantial negative impact of BE on psychological and physiological health, its underlying neural mechanisms are largely unknown. Other repetitive behavior disorders (e.g., obsessive compulsive disorder) show dysfunction within corticostriatal circuitry. However, to date, no work has investigated the in vivo neural dynamics underlying corticostriatal activity during BE episodes. The aim of the current study was to longitudinally examine in vivo neural activity within corticostriatal regions - the infralimbic cortex (IL) and dorsolateral striatum (DLS)- in a robust pre-clinical model for BE. Female C57BL6/J mice (N = 32) were randomized to receive: 1) intermittent (daily, 2-h) binge-like access to palatable food (sweetened condensed milk) (BE), or 2) continuous, non-intermittent (24-h) access to palatable food (control). In vivo calcium imaging was performed via fiber photometry at baseline and after chronic (4 weeks) engagement in the model for BE. Specific consummatory behaviors (feeding bout onset/offset) during recordings were captured using lickometers which generated TTL outputs for precise alignment of behavior to neural data. IL showed no specific changes in neural activity related to BE. However, BE animals showed decreased DLS activity at feeding onset and offset at the chronic timepoint when compared to activity at the baseline timepoint. Additionally, BE mice had significantly lower DLS activity at feeding onset and offset at the chronic timepoint compared to control mice. These results point to a role for DLS hypofunction in chronic BE, highlighting a potential target for future treatment intervention.

The effects of sound in the Balloon Analogue Risk Task.

In this study, we examined the effects of pairing sounds with positive and negative outcomes in the Balloon Analogue Risk Task (BART). A number of published studies using the BART incorporate sounds into the task, where a slot machine or cash register sound is produced when rewards are collected and a popping sound is produced when balloons pop. However, some studies do not use sound, and other studies do not specify whether sound was used. Given that sensory information contributes to the intensity of experiences, it is possible that outcome-related sounds in the BART influence risk-taking behaviors, and inconsistent use of sounds across the many BART variations may affect how results are interpreted. Therefore, the purpose of this study was to investigate the effects of sounds paired with outcomes in the BART, and whether the presence or valence of a sound would systematically alter participants' risk-taking. Across two experiments using Bayesian censored regressions, we show that sounds, regardless of the outcomes they were paired with or their valence, did not affect risk-taking in an adult, non-clinical sample. We consider the implications of these results within methodological and theoretical contexts and encourage researchers to continue dissociating the role of auditory stimuli in feedback processing and subsequent responding.

Learning when to wait and when to act.

Choosing how long to wait in order to optimize reward is a complex decision. We embedded these decisions within a video-game environment in which the amount of reward smoothly increased the longer one waited. The availability of external cues varied in order to determine how they affected the decision to wait to achieve the goal of maximizing the reward rate. As a group, people were most optimal when they could directly observe the growth in reward, and this information overshadowed a static color cue that did not require extended observation. These results were considered within the context of improving the choice between acting versus waiting in order to maximize reward rates.

Mixed effects modeling of Morris water maze data revisited: Bayesian censored regression.

Young, Clark, Goffus, and Hoane (Learning and Motivation, 40(2), 160-177, 2009) documented significant advantages of linear and nonlinear mixed-effects modeling in the analysis of Morris water maze data. However, they also noted a caution regarding the impact of the common practice of ending a trial when the rat had not reached the platform by a preestablished deadline. The present study revisits their conclusions by considering a new approach that involves multilevel (i.e., mixed effects) censored generalized linear regression using Bayesian analysis. A censored regression explicitly models the censoring created by prematurely ending a trial, and the use of generalized linear regression incorporates the skewed distribution of latency data as well as the nonlinear relationships this can produce. This approach is contrasted with a standard multilevel linear and nonlinear regression using two case studies. The censored generalized linear regression better models the observed relationships, but the linear regression created mixed results and clearly resulted in model misspecification.

Turtle, Task Ninja, or Time Waster? Who Cares? Traditional Task-Completion Strategies Are Overrated.

Standard approaches for identifying task-completion strategies, such as precrastination and procrastination, reduce behavior to single markers that oversimplify the process of task completion. To illustrate this point, we consider three task-completion strategies and introduce a new method to identify their use. This approach was tested using an archival data set (N = 8,655) of the available electronic records of research participation at Kansas State University. The approach outperformed standard diagnostic approaches and yielded an interesting finding: Several strategies were associated with negative outcomes. Specifically, both procrastinators and precrastinators struggled to finish tasks on time. Together, these findings underscore the importance of using holistic approaches to determine the relationship among task characteristics, individual differences, and task completion.

The contributions of central and peripheral vision to scene-gist recognition with a 180° visual field.

We investigated the relative contributions of central versus peripheral vision in scene-gist recognition with panoramic 180° scenes. Experiment 1 used the window/scotoma paradigm of Larson and Loschky (2009). We replicated their findings that peripheral vision was more important for rapid scene categorization, while central vision was more efficient, but those effects were greatly magnified. For example, in comparing our critical radius (which produced equivalent performance with mutually exclusive central and peripheral image regions) to that of Larson and Loschky, our critical radius of 10° had a ratio of central to peripheral image area that was 10 times smaller. Importantly, we found different functional relationships between the radius of centrally versus peripherally presented imagery (or the proportion of centrally versus peripherally presented image area) and scene-categorization sensitivity. For central vision, stimulus discriminability was an inverse function of image radius, while for peripheral vision the relationship was essentially linear. In Experiment 2, we tested the photographic-bias hypothesis that the greater efficiency of central vision for rapid scene categorization was due to more diagnostic information in the center of photographs. We factorially compared the effects of the eccentricity from which imagery was sampled versus the eccentricity at which imagery was presented. The presentation eccentricity effect was roughly 3 times greater than the sampling eccentricity effect, showing that the central-vision efficiency advantage was primarily due to the greater sensitivity of central vision. We discuss our results in terms of the eccentricity-dependent neurophysiology of vision and discuss implications for computationally modeling rapid scene categorization.

Variations on the balloon analogue risk task: A censored regression analysis.

In the present project, we reexamined the balloon analogue risk task (BART) by evaluating three variations on the task: one that does not require pumping, one that controls for trial duration, and another that withholds feedback on popping until the end of each trial. To accurately assess the censored data produced by the BART, performance was compared across these variations using Bayesian analysis with censored regression. The first experiment compared a task that required pumping to one that did not, and revealed that the tendency to respond earlier than is optimal does not reflect an avoidance of effort. The second experiment included a condition in which the duration of each trial was held constant by continuing to automatically inflate a balloon to its maximum size after a cash-in response; feedback on the pop time was withheld until the end of each trial. This condition revealed that the tendency to respond earlier is not driven by a desire to finish the task quickly by cashing in early, but the results also strongly suggested that the immediate experience of popping created a greater aversion to risk (although this condition difference was inconsequential by the end of the experiment). The article concludes by considering the implications of these results for cognitive neuroscience approaches to understanding performance on the BART.

Optimal go/no-go ratios to maximize false alarms.

Despite the ubiquity of go/no-go tasks in the study of behavioral inhibition, there is a lack of evidence regarding the impact of key design characteristics, including the go/no-go ratio, intertrial interval, and number of types of go stimuli, on the production of different response classes of central interest. In the present study we sought to empirically determine the optimal conditions to maximize the production of a rare outcome of considerable interest to researchers: false alarms. As predicted, the shortest intertrial intervals (450 ms), intermediate go/no-go ratios (2:1 to 4:1), and the use of multiple types of go stimuli produced the greatest numbers of false alarms. These results are placed within the context of behavioral changes during learning.

Gambling in rhesus macaques (Macaca mulatta): The effect of cues signaling risky choice outcomes.

Preference for a larger-variable "risky" option over a smaller-reliable "safe" option often depends upon the likelihood that the risky option will deliver a sufficiently sized reward to have an equivalent or superior expected value. However, preference for the risky option has been shown to increase under conditions where informative stimuli signaling the outcome of a risky choice is included between the choice and the outcome and this risk-prone preference persists even when the risky option has a lower expected value than the alternative safe option. In the present study, rhesus macaques chose between a risky option and a safe option across two experimental phases to determine whether the outcome signal affected the degree of preference for the risky option. Overall, six out of seven macaques showed a greater preference for the risky option in the signaled condition than in the unsignaled condition. The macaques' risky choices were sensitive to the expected value of the risky option and the signaled condition produced a general increase in risky choices independently of the expected value of the risky outcome. Overall, these results are consistent with those obtained with other animals, and this may relate to a process where animals show a biased preference for "good news." This process may model some of the relevant factors that explain the psychology of gambling in humans.

Using the reassignment procedure to test object representation in pigeons and people.

In four experiments, we evaluated Lea's (1984) reassignment procedure for studying object representation in pigeons (Experiments 1-3) and humans (Experiment 4). In the initial phase of Experiment 1, pigeons were taught to make discriminative button responses to five views of each of four objects. Using the same set of buttons in the second phase, one view of each object was trained to a different button. In the final phase, the four views that had been withheld in the second stage were shown. In Experiment 2, pigeons were initially trained just like the birds in Experiment 1. Then, one view of each object was reassigned to a different button, now using a new set of four response buttons. In Experiment 3, the reassignment paradigm was again tested using the number of pecks to bind together different views of the same object. Across all three experiments, pigeons showed statistically significant generalization of the new response to the non-reassigned views, but such responding was well below that to the reassigned view. In Experiment 4, human participants were studied using the same stimuli and task as the pigeons in Experiment 1. People did strongly generalize the new response to the non-reassigned views. These results indicate that humans, but not pigeons, can employ a unified object representation that they can flexibly map to different responses under the reassignment procedure.

Training Tolerance to Delay Using the Escalating Interest Task.

The present study examined the lasting effects of exposure to reinforcement that increased in magnitude as a function of time between responses in a first-person shooter video game preparation of the escalating interest task. When reinforcement density increased as a function of time, it encouraged participants to wait longer between responses (shots of a weapon). Participants exposed to such contingencies waited significantly longer to fire their weapons than participants who were exposed to linear growth, where long inter-response times were not differentially reinforced. Those with experience in conditions where reinforcement density increased as a function of time showed persistently longer wait times when the contingencies changed in the latter portion of the game where the disincentive to fire quickly was removed. The potential utility of such contingencies for training tolerance to delay of reinforcement and the broader implications of training self-control are discussed.

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.

Temporal prediction errors modulate cingulate-insular coupling.

Prediction error (i.e., the difference between the expected and the actual event's outcome) mediates adaptive behavior. Activity in the anterior mid-cingulate cortex (aMCC) and in the anterior insula (aINS) is associated with the commission of prediction errors under uncertainty. We propose a dynamic causal model of effective connectivity (i.e., neuronal coupling) between the aMCC, the aINS, and the striatum in which the task context drives activity in the aINS and the temporal prediction errors modulate extrinsic cingulate-insular connections. With functional magnetic resonance imaging, we scanned 15 participants when they performed a temporal prediction task. They observed visual animations and predicted when a stationary ball began moving after being contacted by another moving ball. To induced uncertainty-driven prediction errors, we introduced spatial gaps and temporal delays between the balls. Classical and Bayesian fMRI analyses provided evidence to support that the aMCC-aINS system along with the striatum not only responds when humans predict whether a dynamic event occurs but also when it occurs. Our results reveal that the insula is the entry port of a three-region pathway involved in the processing of temporal predictions. Moreover, prediction errors rather than attentional demands, task difficulty, or task duration exert an influence in the aMCC-aINS system. Prediction errors debilitate the effect of the aMCC on the aINS. Finally, our computational model provides a way forward to characterize the physiological parallel of temporal prediction errors elicited in dynamic tasks.

The importance of solid-phase distribution on the oral bioaccessibility of Ni and Cr in soils overlying Palaeogene basalt lavas, Northern Ireland.

Potentially toxic elements (PTEs) including nickel and chromium are often present in soils overlying basalt at concentrations above regulatory guidance values due to the presence of these elements in underlying geology. Oral bioaccessibility testing allows the risk posed by PTEs to human health to be assessed; however, bioaccessibility is controlled by factors including mineralogy, particle size, solid-phase speciation and encapsulation. X-ray diffraction was used to characterise the mineralogy of 12 soil samples overlying Palaeogene basalt lavas in Northern Ireland, and non-specific sequential extraction coupled with chemometric analysis was used to determine the distribution of elements amongst soil components in 3 of these samples. The data obtained were related to total concentration and oral bioaccessible concentration to determine whether a relationship exists between the overall concentrations of PTEs, their bioaccessibility and the soils mineralogy and geochemistry. Gastric phase bioaccessible fraction (BAF %) ranged from 0.4 to 5.4 % for chromium in soils overlying basalt and bioaccessible and total chromium concentrations are positively correlated. In contrast, the range of gastric phase BAF for nickel was greater (1.4-43.8 %), while no significant correlation was observed between bioaccessible and total nickel concentrations. However, nickel BAF was inversely correlated with total concentration. Solid-phase fractionation information showed that bioaccessible nickel was associated with calcium carbonate, aluminium oxide, iron oxide and clay-related components, while bioaccessible chromium was associated with clay-related components. This suggests that weathering significantly affects nickel bioaccessibility, but does not have the same effect on the bioaccessibility of chromium.

Resource limitations: A taxonomy.

Decision making within the context of resource limitations requires balancing the short-term benefits of obtaining a resource and the long-term consequences of depleting those resources. The present manuscript focuses on four types of tasks that share this tradeoff to develop a taxonomy that will encourage a deeper understanding of the psychological processes at play. The four types considered are foraging, common pool traps, deterioration traps, and a novel designation referred to as resource cliffs. All four will be shown to include two opposite processes - depletion of the resource and its replenishment over time. By considering the unique and shared features of these tasks, a taxonomy of features emerges that can be combined to not only create novel tasks but also to shift the research focus to task features rather than specific tasks. The paper closes with a consideration of current theoretical frameworks previously applied to one or more of these resource-limitation tasks as well as the promise of reinforcement learning as a unifying theory.

When Smaller Sooner Depletes a Pool of Resources Faster.

Behavior has short-term (proximal) and long-term (distal) consequences, and these consequences often involve different commodities. In particular, a commonly encountered distal consequence involves running out of resources - energy to respond, available food, ammunition, or money in the bank - that must be replenished before continuing a rewarding task. The current project examines proximal behavioral consequences in a video game (the amount of damage done to a clicked-on target as a function of waiting) and distal behavioral consequences (running out of the resources that allow the player to click on a target). When depleted, the resource replenished after a fixed amount of time. Thus, participants sometimes faced a tradeoff between behaviors that maximized their short-term reward rate and those that maximized their long-term reward rate. When the proximal contingency did not affect the short-term reward rate, the mere presence of limitations resulted in the slower use of resources, but the slowdown did not evidence strong sensitivity to the size of the resource pool nor the delay to its replenishment (Experiment 1). However, when the proximal contingency rewarded faster use of resources, participants did show sensitivity to the duration of the replenishment delay and the size of the resource pool (Experiment 2).

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.

Longitudinal assessment of cognitive function in the APPswe/PS1dE9 mouse model of Alzheimer's-related beta-amyloidosis.

Preclinical models of Alzheimer's disease (AD)-related cognitive decline can be useful for developing therapeutics. The current study longitudinally assessed short-term memory, using a delayed matching-to-position (DMTP) task, and attention, using a 3-choice serial reaction time (3CSRT) task, from approximately 18 weeks of age through death or 72 weeks of age in APPswe/PS1dE9 mice, a widely used mouse model of AD-related amyloidosis. Both transgenic (Tg) and non-Tg mice exhibited improvements in DMTP accuracy over time. Breaks in testing reduced DMTP accuracy but accuracy values quickly recovered in both Tg and non-Tg mice. Both Tg and non-Tg mice exhibited high accuracy in the 3CSRT task with breaks in testing briefly reducing accuracy values equivalently in the 2 genotypes. The current results raise the possibility that deficits in Tg APPswe/PS1dE9 mice involve impairments in learning rather than declines in established performances. A better understanding of the factors that determine whether deficits develop will be useful for designing evaluations of potential pharmacotherapeutics and may reveal interventions for clinical application.

Variations on variability: effects of display composition on same-different discrimination in pigeons.

Discriminating same from different multiitem arrays can be represented as a discrimination between arrays involving low variability and arrays involving high variability. In the present investigation, we first trained pigeons with the extreme values along the variability continuum (arrays containing 16 identical items vs. 16 nonidentical items), and we later tested the birds with arrays involving intermediate levels of variability; we created these testing arrays either by manipulating the combination of same and different items (mixture testing) or by changing the number of items in the same and different arrays (number testing). According to an entropy account (Young & Wasserman, Journal of Experimental Psychology: Animal Behavior Processes 23:157-170, 1997), the particular means of changing variability should have no effect on same-different discrimination performance: Equivalent variability should yield equivalent performance. In this critical test of an entropy account, we found that entropy could explain a large portion of our data, but not the entire collection of results.

Rich stimulus sampling for between-subjects designs improves model selection.

The choice of stimulus values to test in any experiment is a critical component of good experimental design. This study examines the consequences of random and systematic sampling of data values for the identification of functional relationships in experimental settings. Using Monte Carlo simulation, uniform random sampling was compared with systematic sampling of two, three, four, or N equally spaced values along a single stimulus dimension. Selection of the correct generating function (a logistic or a linear model) was improved with each increase in the number of levels sampled, with N equally spaced values and random stimulus sampling performing similarly. These improvements came at a small cost in the precision of the parameter estimates for the generating function.