Shifts in postdiscrimination gradients within a stimulus dimension based on bilateral facial symmetry

Waist-to-Hip Ratio as Supernormal Stimuli: Effect of Contrapposto Pose and Viewing Angle

In women, the waist-to-hip ratio (WHR) is an indicator of attractiveness, health, youthfulness, and reproductive potential. In the current study, we hypothesized that viewing angle and body postures influence the attractiveness of these forms based on the view dependency of WHR stimuli (vdWHR). Using eye tracking, we quantified the number of fixations and dwell time on 3D images of a female avatar in two different poses (standing and contrapposto) from eight viewing angles incrementing in 45 degrees of rotation. A total of 68 heterosexual individuals (25 men and 43 women) participated in the study. Results showed that the contrapposto pose was perceived as more attractive than the standing pose and that lower vdWHR sides of the stimuli attracted more first fixation, total fixations, and dwell time. Overall, the results supported that WHR is view-dependent and vdWHRs lower than optimal WHRs are supernormal stimuli that may generate peak shifts in responding. Results are discussed in terms of the attractiveness of women's movements (gaits and dance) and augmented artistic presentations.

A jump to the left and a step to the right: A test of two accounts of peak shift

“Peak Shift” usually occurs following intradimensional-discrimination training and involves a shift of the peak of the generalization gradient away from the original discriminative stimulus (S+) in a direction away from an S-. Two theoretical accounts of peak shift, the gradient interaction theory (GIT) and adaptation level theory (ALT), were compared. The effects of asymmetric test stimuli and the impact of instructions to participants for them to treat stimuli as members of categories on generalization gradients were investigated. In Experiment 1, the relation between peak shifts obtained when an extended asymmetric set of test stimuli was employed and the occurrence of categorization of the stimuli involved was investigated in four separate conditions. Two involved temporal discrimination, one involved line-angle discrimination, and one involved a compound line-angle and temporal cue discrimination. If participants treated the stimuli as belonging to discrete categories, such as hands-on a clock, rather than as being on continuous dimensions then responding to the compound cue was expected to result in attenuation of blocking of a peak shift. However, the peak shift obtained to the three cue types were the same. In Experiment 2, an independent group of participants was given explicit instructions to treat the line angles as if they were the hands of a clock face and this eliminated peak shift. The results from the present experiments support an ALT interpretation, although the peak shifts were significantly smaller in magnitude than predicted by this account.

Dopamine regulates stimulus generalization in the human hippocampus

The ability to generalize previously learned information to novel situations is fundamental for adaptive behavior. However, too wide or too narrow generalization is linked to neuropsychiatric disorders. Previous research suggests that interactions between the dopaminergic system and the hippocampus may play a role in generalization, but whether and how the degree of generalization can be modulated via these pathways is currently unknown. Here, we addressed this question in humans using pharmacology, functional magnetic resonance imaging, and computational modeling. Blocking dopamine D2-receptors (D2R) altered generalization behavior as revealed by an increased kurtosis of the generalization gradient, and a decreased width of model-derived generalization parameters. Moreover, D2R-blockade modulated similarity-based responses in the hippocampus and decreased midbrain-hippocampal connectivity, which in turn correlated with individual differences in generalization. These results suggest that dopaminergic activity in the hippocampus may relate to the degree of generalization and highlight a potential target for treatment.

Individual differences during acquisition predict shifts in generalization

Learning to distinguish subtle differences in objects or events can impact how one generalizes. In some cases, training can cause novel events to appear more familiar or attractive than those actually experienced during training: the peak shift effect. This study examined whether individual differences in learning led to systematic patterns of generalization. Participants were trained to identify simulated birdsongs, and then tested on their ability to identify a target song presented among several similar songs that differed in pitch. Initial analysis showed that those attaining moderate proficiency at discriminating songs during training were more likely to shift than those performing poorly or proficiently. However, a neural network trained to output individuals' gradient dynamics using only performance during training as input found an additional set of training variables that predicted shift. Specifically, one subset of shifters had highly conservative response biases accompanied by very little change to perceptual sensitivity in training. These findings suggest that discrimination learning may only lead to generalization shifts in some individuals, and that all individuals who shift may not do so for the same reason.

Is the pathogenic ergot fungus a conditional defensive mutualist for its host grass?

It is well recognized, that outcomes of mutualistic plant-microorganism interactions are often context dependent and can range from mutualistic to antagonistic depending on conditions. Instead, seemingly pathogenic associations are generally considered only harmful to plants. The ergot fungus (Claviceps purpurea) is a common seed pathogen of grasses and cereals. Ergot sclerotia contain alkaloids which can cause severe toxicity in mammals when ingested, and thus the fungal infection might provide protection for the host plant against mammalian herbivores. Theoretically, the net effect of ergot infection would positively affect host seed set if the cost is not too high and the defensive effect is strong enough. According to our empirical data, this situation is plausible. First, we found no statistically significant seed loss in wild red fescue (Festuca rubra) inflorescences due to ergot infection, but the seed succession decreased along increasing number of sclerotia. Second, in a food choice experiment, sheep showed avoidance against forage containing ergot. Third, the frequency of ergot-infected inflorescences was higher in sheep pastures than surrounding ungrazed areas, indicating a protective effect against mammalian grazing. We conclude that, although ergot can primarily be categorized as a plant pathogen, ergot infection may sometimes represent indirect beneficial effects for the host plant. Ergot may thus serve as a conditional defensive mutualist for its host grass, and the pathogenic interaction may range from antagonistic to mutualistic depending on the situation.

How glitter relates to gold: similarity-dependent reward prediction errors in the human striatum

Optimal choices benefit from previous learning. However, it is not clear how previously learned stimuli influence behavior to novel but similar stimuli. One possibility is to generalize based on the similarity between learned and current stimuli. Here, we use neuroscientific methods and a novel computational model to inform the question of how stimulus generalization is implemented in the human brain. Behavioral responses during an intradimensional discrimination task showed similarity-dependent generalization. Moreover, a peak shift occurred, i.e., the peak of the behavioral generalization gradient was displaced from the rewarded conditioned stimulus in the direction away from the unrewarded conditioned stimulus. To account for the behavioral responses, we designed a similarity-based reinforcement learning model wherein prediction errors generalize across similar stimuli and update their value. We show that this model predicts a similarity-dependent neural generalization gradient in the striatum as well as changes in responding during extinction. Moreover, across subjects, the width of generalization was negatively correlated with functional connectivity between the striatum and the hippocampus. This result suggests that hippocampus-striatal connections contribute to stimulus-specific value updating by controlling the width of generalization. In summary, our results shed light onto the neurobiology of a fundamental, similarity-dependent learning principle that allows learning the value of stimuli that have never been encountered.

Predicting shifts in generalization gradients with perceptrons

Perceptron models have been used extensively to model perceptual learning and the effects of discrimination training on generalization, as well as to explore natural classification mechanisms. Here, we assess the ability of existing models to account for the time course of generalization shifts that occur when individuals learn to distinguish sounds. A set of simulations demonstrates that commonly used single-layer and multilayer perceptron networks do not predict transitory shifts in generalization over the course of training but that such dynamics can be accounted for when the output functions of these networks are modified to mimic the properties of cortical tuning curves. The simulations further suggest that prudent selection of stimuli and training criteria can allow for more precise predictions of learning-related shifts in generalization gradients in behavioral experiments. In particular, the simulations predict that individuals will show maximal peak shift after different numbers of trials, that easier contrasts will lead to slower development of shifted peaks, and that whether generalization shifts persist or dissipate will depend on which stimulus dimensions individuals use to distinguish stimuli and how those dimensions are neurally encoded.

Translational contributions of the experimental analysis of behavior

It has been argued that to increase societal impact behavioral researchers must do more to address problems of obvious practical importance. The basic science wing of behavior analysis has been described as especially detached from this goal, but is it really necessary that basic science demonstrate social relevance? If so, why hasn't this occurred more often, and what can be done to improve the status quo? To address these questions and to stimulate discussion about the future of basic behavior science, I describe two widely embraced arguments in favor of pure basic science (that which is undertaken without concern for practical applications); explain why a translational research agenda is likely to better recruit tangible support for basic science; propose that addressing practical problems does not require basic science to abandon its focus on fundamental principles; and identify some possible impediments to translational innovation that may need to be addressed for basic behavior science to increase its translational footprint.

Translational research in behavior analysis: historical traditions and imperative for the future

"Pure basic" science can become detached from the natural world that it is supposed to explain. "Pure applied" work can become detached from fundamental processes that shape the world it is supposed to improve. Neither demands the intellectual support of a broad scholarly community or the material support of society. Translational research can do better by seeking innovation in theory or practice through the synthesis of basic and applied questions, literatures, and methods. Although translational thinking has always occurred in behavior analysis, progress often has been constrained by a functional separation of basic and applied communities. A review of translational traditions in behavior analysis suggests that innovation is most likely when individuals with basic and applied expertise collaborate. Such innovation may have to accelerate for behavior analysis to be taken seriously as a general-purpose science of behavior. We discuss the need for better coordination between the basic and applied sectors, and argue that such coordination compromises neither while benefiting both.