Searching for nothing: placing zero on the temporal continuum.

Generalization allows responses acquired in one situation to be transferred to similar situations. For temporal stimuli, a discontinuity has been found between zero and non-zero durations: responses in trials with no (or 0-s) stimuli and in trials with very short stimuli differ more than what would be expected by generalization. This discontinuity may happen because 0-s durations do not belong to the same continuum as non-zero durations. Alternatively, the discontinuity may be due to generalization decrement effects: a 0-s stimulus differs from a short stimulus not only in duration, but also in its presence, thus leading to greater differences in performance. Aiming to reduce differences between trials with and without a stimulus, we used two procedures to test whether a potential reduction in generalization decrement would bring performance following zero and non-zero durations closer. In both procedures, there was a reduction in the discontinuity between 0-s and short durations, supporting the hypothesis that 0-s durations are integrated in the temporal subjective continuum.

Computational models of stimulus equivalence: An intersection for the study of symbolic behavior.

Stimulus equivalence is a central paradigm in the analysis of symbolic behavior, language, and cognition. It describes emergent relations between stimuli that were not explicitly trained and cannot be explained by primary stimulus generalization. In recent years, researchers have developed computational models to simulate the learning of equivalence relations. These models have been used to address primary theoretical and methodological issues in this field, such as exploring the underlying mechanisms that explain emergent equivalence relations and analyzing the effects of training and testing protocols on equivalence outcomes. Nonetheless, although these models build upon general learning principles, their operation is usually obscure for nonmodelers, and in the field of stimulus equivalence computational models have been developed with a variety of approaches, architectures, and algorithms that make it difficult to understand the scope and contributions of these tools. In this paper, we present the state of the art in computational modeling of stimulus equivalence. We seek to provide concise and accessible descriptions of the models' functioning and operation, highlight their main theoretical and methodological contributions, identify the existing software available for researchers to run experiments, and suggest future directions in the emergent field of computational modeling of stimulus equivalence.

Individual differences in stimulus identification, rule induction, and generalization of learning.

In the field of stimulus generalization, an old yet unresolved discussion pertains to what extent stimulus misidentifications contribute to the pattern of conditioned responding. In this article, we perform cluster analysis on six datasets (four published datasets and two unpublished datasets, included N = 950) to examine the relationship between interindividual differences in (a) stimulus identification, (b) patterns of generalized responding, and (c) verbalized generalization rules. The datasets were obtained from online predictive learning tasks where participants learned associations between colored cues and the presence or absence of a hypothetical outcome. In these datasets, stimulus identification and expectancy ratings were assessed in separate phases to a range of colors varying between blue-green. Using cluster analyses on performance during stimulus identification, we identified different subgroups of participants (good vs. bad identifiers). In all six datasets, we found a close relationship between the pattern of stimulus identification and the shape of the expectancy gradient across the test dimension between the identified subgroups. Furthermore, participants classified as good identifiers were more likely to report a similarity generalization rule than a relational or linear rule, suggesting that individual differences in stimulus identification are related to individual differences in generalization rules. These findings suggest that greater consideration should be given to interindividual variability in stimulus identification, inductive rules, and their relationship in explaining patterns of generalized responses. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Modeling relational responding with artificial neural networks.

Relational responding refers to behavior that conforms to a rule for com- paring stimuli. Lazareva et al. (2014) trained pigeons to choose either the smaller or the larger of two circles, using 1-3 pairs of circles for training and 17-19 new pairs for testing. The pigeons showed relational responding on some test pairs and systematic failures on others. We present a simple artificial neural network model that reproduces the animals' behavior well, similarly to Lazareva et al.'s (2014) statistical model based on stimulus features and stimulus relationships. We analyze how the network model gener- alizes from training to test stimuli, and show that it can reconcile contrasting ideas about relational responding from the seminal works by Köhler (1929, 1918/1938, 1924), positing that animals can learn relational rules such as "choose the larger stimulus," and Spence (1937), positing that relational re- sponding can be explained based on stimulus generalization.

Generalization following symmetrical intradimensional discrimination training.

A challenge for generalization models is to specify how excitation generated from a CS+ (i.e., positive evidence) should interact with inhibition from a CS- (i.e., negative evidence) to produce generalized responding. Empirically, many generalization phenomena are consistent with the monotonicity principle, which states that additional positive evidence should increase generalized responding, whereas additional negative evidence should decrease responding. However, a recent study (Lee et al.,, 2019) demonstrated that additional negative evidence can sometimes increase generalization, in direct contrast to animal data and associative accounts of generalization. The current study investigated whether a similar effect could be found in a symmetrical intradimensional discrimination procedure with two sources of negative evidence (CS-s) located on each side of a CS+. In three experiments, we compared generalization along a green-blue dimension between one group of participants who learned that an aqua-colored shape (CS+) predicted an outcome (Single Positive group) with another group who also learned that both a slightly greener and a slightly bluer shape led to no outcome (Double Negative group). Experiments 1A and 1B showed no effect of the additional negative evidence in increasing generalization around the CS+. However, changing a stimulus feature at test (shape) resulted in a higher gradient peak in the Double Negative group relative to the Single Positive group in Experiment 2. Although this result violates the monotonicity principle, an extended version of Blough's (1975) model applying cue competition to multiple stimulus dimensions (i.e., shape and color) successfully replicated the group differences. Our results suggest that associative mechanisms can account for some instances in which negative evidence increases generalization. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

A response function that maps associative strengths to probabilities.

Bridging associative and normative theories of animal learning, I show that an associative system can behave as if performing probabilistic inference by using the function f(V) = 1 - e-cV to transform associative strengths (V) into response probabilities. For example, using this function, an associative system can respond normatively to a compound stimulus AB, given previous separate experiences with the components A and B. The CR probability formulae that result from the proposed function have a normative interpretation in terms of statistical decision theory. The formulae also suggest a normative interpretation of stimulus generalization as a heuristic to infer whether different stimuli are likely to convey redundant or independent information about reinforcement. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

Choosing a future from a murky past: A generalization-based model of behavior.

Remembering the past appears critical in allowing organisms to detect order in an environment, and hence to behave in accordance with likely future events. Yet the shortcomings of remembering and perceiving typically mean that the remembered past differs from the actual past, and hence that behavior does not perfectly track the structure of the environment. Here, we outline how the process of generalization might be used to understand differences between what an organism does, and the structure of the past and potential structure of the environment. We explore how different sources of generalization - both from within the same stimulus situation, and from different stimulus situations - might be modeled quantitatively, and how predictions made by this modeling approach are supported by research. Finally, we discuss how generalization from multiple stimulus situations, longer-term experience, and from stimulus situations in the past that are not identical to the stimulus situation in the present, might contribute to our understanding of how an organism's experience translates into behavior.

La importancia de la estimulación a través de los colores / The importance of stimulation through colors

Este documento pretende hacer reflexionar sobre la importancia de los colores, tanto en el ámbito laboral como en el personal. Trata de plantear la policromía como una herramienta de estimulación, un ejemplo de diversidad y un camino para alcanzar el bienestar. (AU)

This document pretends to reflect on the importance of colors, both in professional field and in the personal. It tries to pose polychromy like a stimulation tool, an example of diversity and a way to wellness. (AU)

Stimulus Generalization in Mice during Pavlovian Eyeblink Conditioning.

Here, we investigate stimulus generalization in a cerebellar learning paradigm, called eyeblink conditioning. Mice were conditioned to close their eyes in response to a 10-kHz tone by repeatedly pairing this tone with an air puff to the eye 250 ms after tone onset. After 10 consecutive days of training, when mice showed reliable conditioned eyelid responses to the 10-kHz tone, we started to expose them to tones with other frequencies, ranging from 2 to 20 kHz. We found that mice had a strong generalization gradient, whereby the probability and amplitude of conditioned eyelid responses gradually decreases depending on the dissimilarity with the 10-kHz tone. Tones with frequencies closest to 10 kHz evoked the most and largest conditioned eyelid responses and each step away from the 10-kHz tone resulted in fewer and smaller conditioned responses (CRs). In addition, we found that tones with lower frequencies resulted in CRs that peaked earlier after tone onset compared with those to tones with higher frequencies. Together, our data show prominent generalization patterns in cerebellar learning. Since the known function of cerebellum is rapidly expanding from pure motor control to domains that include cognition, reward-learning, fear-learning, social function, and even addiction, our data imply generalization controlled by cerebellum in all these domains.

Learning-induced biases in the ongoing dynamics of sensory representations predict stimulus generalization.

Sensory stimuli have long been thought to be represented in the brain as activity patterns of specific neuronal assemblies. However, we still know relatively little about the long-term dynamics of sensory representations. Using chronic in vivo calcium imaging in the mouse auditory cortex, we find that sensory representations undergo continuous recombination, even under behaviorally stable conditions. Auditory cued fear conditioning introduces a bias into these ongoing dynamics, resulting in a long-lasting increase in the number of stimuli activating the same subset of neurons. This plasticity is specific for stimuli sharing representational similarity to the conditioned sound prior to conditioning and predicts behaviorally observed stimulus generalization. Our findings demonstrate that learning-induced plasticity leading to a representational linkage between the conditioned stimulus and non-conditioned stimuli weaves into ongoing dynamics of the brain rather than acting on an otherwise static substrate.

Fear conditioning and stimulus generalization in association with age in children and adolescents.

The aim of the study was to investigate age-related differences in fear learning and generalization in healthy children and adolescents (n = 133), aged 8-17 years, using an aversive discriminative fear conditioning and generalization paradigm adapted from Lau et al. (2008). In the current task, participants underwent 24 trials of discriminative conditioning of two female faces with neutral facial expressions, with (CS+) or without (CS-) a 95-dB loud female scream, presented simultaneously with a fearful facial expression (US). The discriminative conditioning was followed by 72 generalization trials (12 CS+, 12 GS1, 12 GS2, 12 GS3, 12 GS4, and 12 CS-): four generalization stimuli depicting gradual morphs from CS+ to CS- in 20%-steps were created for the generalization phases. We hypothesized that generalization in children and adolescents is negatively correlated with age. The subjective ratings of valence, arousal, and US expectancy (the probability of an aversive noise following each stimulus), as well as skin conductance responses (SCRs) were measured. Repeated-measures ANOVAs on ratings and SCR amplitudes were calculated with the within-subject factors stimulus type (CS+, CS-, GS1-4) and phase (Pre-Acquisition, Acquisition 1, Acquisition 2, Generalization 1, Generalization 2). To analyze the modulatory role of age, we additionally calculated ANCOVAs considering age as covariate. Results indicated that (1) subjective and physiological responses were generally lower with increasing age irrespective to the stimulus quality, and (2) stimulus discrimination improved with increasing age paralleled by reduced overgeneralization in older individuals. Longitudinal follow-up studies are required to analyze fear generalization with regard to brain maturational aspects and clarify whether overgeneralization of conditioned fear promotes the development of anxiety disorders or vice versa.

Design and evaluation of a touchscreen apparatus for operant research with pigeons.

We developed a touchscreen apparatus for pigeons and conducted a series of experiments that assessed its utility for free-operant procedures. The apparatus incorporated an on-board Windows computer, an electromechanical interface, an amplified speaker, and the touchscreen. We found that merely projecting a virtual key on the screen was insufficient; too many pecks missed the key. Adding a visual target in the center of the key and providing visual feedback for on-key pecks both failed to improve response accuracy. Accuracy was improved by imposing a timeout after off-key pecks or providing a physical boundary around the key. With the physical boundary, response accuracy was comparable to that obtained with conventional plastic keys, and response acquisition via autoshaping also was comparable. Mixing the color elements of the screen's pixels produced color stimuli, but the colors did not function as pure wavelengths of light in tests of stimulus generalization. Both colors and geometric shapes functioned as discriminative stimuli in multiple schedules with variable-interval and extinction components or rich and lean fixed-ratio components. In general, our touchscreen apparatus is a viable alternative to conventional pigeon chambers and increases the experimenter's options for visual stimuli, auditory stimuli, and the number and location of response keys.

Exploration of physiological sensors, features, and machine learning models for pain intensity estimation.

In current clinical settings, typically pain is measured by a patient's self-reported information. This subjective pain assessment results in suboptimal treatment plans, over-prescription of opioids, and drug-seeking behavior among patients. In the present study, we explored automatic objective pain intensity estimation machine learning models using inputs from physiological sensors. This study uses BioVid Heat Pain Dataset. We extracted features from Electrodermal Activity (EDA), Electrocardiogram (ECG), Electromyogram (EMG) signals collected from study participants subjected to heat pain. We built different machine learning models, including Linear Regression, Support Vector Regression (SVR), Neural Networks and Extreme Gradient Boosting for continuous value pain intensity estimation. Then we identified the physiological sensor, feature set and machine learning model that give the best predictive performance. We found that EDA is the most information-rich sensor for continuous pain intensity prediction. A set of only 3 features from EDA signals using SVR model gave an average performance of 0.93 mean absolute error (MAE) and 1.16 root means square error (RMSE) for the subject-independent model and of 0.92 MAE and 1.13 RMSE for subject-dependent. The MAE achieved with signal-feature-model combination is less than 1 unit on 0 to 4 continues pain scale, which is smaller than the MAE achieved by the methods reported in the literature. These results demonstrate that it is possible to estimate pain intensity of a patient using a computationally inexpensive machine learning model with 3 statistical features from EDA signal which can be collected from a wrist biosensor. This method paves a way to developing a wearable pain measurement device.

Neural substrates of human fear generalization: A 7T-fMRI investigation.

Fear generalization - the tendency to interpret ambiguous stimuli as threatening due to perceptual similarity to a learned threat - is an adaptive process. Overgeneralization, however, is maladaptive and has been implicated in a number of anxiety disorders. Neuroimaging research has indicated several regions sensitive to effects of generalization, including regions involved in fear excitation (e.g., amygdala, insula) and inhibition (e.g., ventromedial prefrontal cortex). Research has suggested several other small brain regions may play an important role in this process (e.g., hippocampal subfields, bed nucleus of the stria terminalis [BNST], habenula), but, to date, these regions have not been examined during fear generalization due to limited spatial resolution of standard human neuroimaging. To this end, we utilized the high spatial resolution of 7T fMRI to characterize the neural circuits involved in threat discrimination and generalization. Additionally, we examined potential modulating effects of trait anxiety and intolerance of uncertainty on neural activation during threat generalization. In a sample of 31 healthy undergraduate students, significant positive generalization effects (i.e., greater activation for stimuli with increasing perceptual similarity to a learned threat cue) were observed in the visual cortex, thalamus, habenula and BNST, while negative generalization effects were observed in the dentate gyrus, CA1, and CA3. Associations with individual differences were underpowered, though preliminary findings suggested greater generalization in the insula and primary somatosensory cortex may be correlated with self-reported anxiety. Overall, findings largely support previous neuroimaging work on fear generalization and provide additional insight into the contributions of several previously unexplored brain regions.

Stimulus generalization of behavioral history: Interspecies generality and persistence of generalization gradients.

Four pigeons were exposed to a tandem variable-interval (VI) fixed-ratio (FR) schedule in the presence of a 50-pixel (about 15 mm) square or an 80-pixel (about 24 mm) square and to a tandem VI differential-reinforcement-of-low-rate (DRL) schedule when a second 80-pixel or 50-pixel square was present. The values of the VI and FR schedules were adjusted to equate reinforcement rates in the two tandem schedules. Following this, a square-size continuum generalization test was administered under a fixed-interval (FI) schedule or extinction. In the first testing session, response frequency was a graded function of the similarity of the test stimuli to the training stimuli for all pigeons. These systematic generalization gradients persisted longer under the FI schedule than under extinction.

Sex differences in the discriminative stimulus characteristics of a morphine occasion setter in rats.

The current study investigated whether the stimulus effects of morphine can function as a positive and negative feature in a Pavlovian occasion setting drug discrimination preparation in male and female rats. Sprague-Dawley rats were assigned to a feature positive (FP) or feature negative (FN) training group and all received intermixed morphine (3.2 mg/kg, IP) or saline injections 15 min before 20-min daily training sessions. For FP rats, on morphine sessions, each of eight 15-s white noise (WN) presentations was followed by 4-s access to sucrose (0.01 ml, 26% w/v); on saline sessions, sucrose was withheld. FN rats learned the reverse contingency. FP discrimination was acquired somewhat sooner than FN discrimination, and females, but not males, became sensitized to the locomotor effects of morphine, which did not influence conditioned responding. Rats then entered dose generalization testing. There was no sex difference in dose generalization for FN groups (ED50 1.26 for males and 1.57 for females). Yet for FP rats, the dose response curve for females was shifted to the right compared to males (ED50 0.54 for males and 1.94 for females). FP females exhibited enhanced responding at a dose higher than that of their original training. These findings reveal the need to reassess our notions of drug stimuli that guide appropriate associative behaviours from the perspective of sex differences.

Knockout serotonin transporter in rats moderates outcome and stimulus generalization.

Understanding the common dimension of mental disorders (such as anxiety, depression, and drug addiction) might contribute to the construction of biological frameworks (Research Domain Criteria, RDoC) for novel ways of treatment. One common dimension at the behavioral level observed across these disorders is a generalization. Testing generalization in serotonin transporter (5-HTT) knockout (KO) rats, an animal model showing depression/anxiety-like behaviors and drug addiction-like behaviors, could therefore provide more insights into this framework. We tested the outcome and stimulus generalization in wild-type (WT) and 5-HTT KO rats. Using a newly established touchscreen-based task, subjects directly responded to visual stimuli (Gabor patch images). We measured the response time and outcome in a precise manner. We found that 5-HTT KO rats processed visual information faster than WT rats during outcome generalization. Interestingly, during stimulus generalization, WT rats gradually responded faster to the stimuli as the sessions progressed, while 5-HTT KO rats responded faster than WT in the initial sessions and did not change significantly as the sessions progressed. This observation suggests that KO rats, compared to WT rats, may be less able to update changes in information. Taken together, KO 5-HTT modulates information processing when the environment changes.

The influence of correlations between noncritical features and reinforcement on stimulus generalization.

One strategy to program for generalization is to vary noncritical features in teaching exemplars, thereby avoiding noncritical features from being highly correlated with reinforcement and thus gaining faulty stimulus control. In the current translational evaluation, 2 groups of adults of typical development were taught to respond to arbitrary stimuli with experimenter-defined critical and noncritical features in a matching-to-sample task. The teaching arrangement used for 1 group programmed for low correlation between noncritical features and reinforcement; the teaching arrangement used for the other group programmed for high correlation between noncritical features and reinforcement. Participants in the former group displayed (a) faster acquisition of matching, (b) less variability in correct responding, and (c) a decreased likelihood of faulty stimulus control developing during training. The results contribute towards advancing the study of stimulus control and developing an explicit technology of generalization to better serve consumers of the application of our science.

The influence of reward magnitude on stimulus memory and stimulus generalization in categorization decisions.

Reward magnitude is a central concept in most theories of preferential decision making and learning. However, it is unknown whether variable rewards also influence cognitive processes when learning how to make accurate decisions (e.g., sorting healthy and unhealthy food differing in appeal). To test this, we conducted 3 studies. Participants learned to classify objects with 3 feature dimensions into two categories before solving a transfer task with novel objects. During learning, we rewarded all correct decisions, but specific category exemplars yielded a 10 times higher reward (high vs. low). Counterintuitively, categorization performance did not increase for high-reward stimuli, compared with an equal-reward baseline condition. Instead, performance decreased reliably for low-reward stimuli. To analyze the influence of reward magnitude on category generalization, we implemented an exemplar-categorization model and a cue-weighting model using a Bayesian modeling approach. We tested whether reward magnitude affects (a) the availability of exemplars in memory, (b) their psychological similarity to the stimulus, or (c) attention to stimulus features. In all studies, the evidence favored the hypothesis that reward magnitude affects the similarity gradients of high-reward exemplars compared with the equal-reward baseline. The results from additional reward-judgment tasks (Studies 2 and 3) strongly suggest that the cognitive processes of reward-value generalization parallel those of category generalization. Overall, the studies provide insights highlighting the need for integrating reward- and category-learning theories. (PsycInfo Database Record (c) 2020 APA, all rights reserved).

The improvement of infants exclusive breastfeeding through the intervention of DC motor vibratory (DMV) to postpartum mother in USU Medan hospital

OBJECTIVE: To determine the effect of DMV on the success of exclusive breastfeeding. METHOD: This research is a quasi-experimental with control group design. The sample of this study was 76 postpartum mothers each in the intervention 38 and control groups 38. The instruments used were demographic data and exclusive breastfeeding. The intervention was DMV which was carried out for postpartum mothers for 6 months. Data analysis uses independent t-test. RESULTS: The results showed that an increase in exclusive breastfeeding for postpartum mothers through the DMV program in Medan City, p = 0.03 (p < 0.05) with a mean intervention of 5.55, SD 0.82 and a mean control of 5.13, SD 0.83. CONCLUSIONS: The intervention of exclusive breastfeeding is very important to increase the amount of breastfeeding in postpartum mothers. This intervention is expected to be carried out regularly in the community

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