Learned Behavior Research Articles

Perceptual variability: Implications for learning and generalization.

The generalization of learned behavior has been extensively investigated, but accounting for variance in generalized responding remains a challenge. Based on recent advances, we demonstrate that the inclusion of perceptual measures in generalization research may lead to a better understanding of both intra- and interindividual differences in generalization. We explore various ways through which perceptual variability can influence generalized responding. We investigate its impact on the ability to discriminate between stimuli and how similarity between stimuli may be variable, rather than fixed, because of it. Subsequently, we argue that perceptual variations can yield different learning experiences and that interindividual differences in generalized responding may be understood from this perspective. Finally, we point to the role of memory and decision-making within this context. Throughout this paper, we argue that accounting for perception in current generalization protocols will improve the precision of obtained generalization gradients and the ability to infer latent mechanisms. This can inspire future attempts to use generalization gradients as a (clinical) predictor or to relate them to individual traits and neural correlates and, ultimately, may lead to new theoretical and clinical insights.

Self-Regulation Without Force: Can Awareness Leverage Reward to Drive Behavior Change?

To reach longer-term goals and live aligned with their values, people typically must regulate their behavior. Effortful self-control is one way to achieve this and is usually framed as a forceful struggle between lower-level impulses and higher-level cognitive control processes. For example, people may restrain themselves from eating cake in order to lose weight. An alternative avenue of self-regulation draws on autonomous motivation: Individuals eat healthfully because it is values-congruent or intrinsically satisfying. Recent advances in the understanding of reward valuation on a neural level (e.g., ventromedial prefrontal cortex/orbitofrontal cortex) and emerging treatments on a clinical level (e.g., mindfulness training) suggest a possible mechanistic convergence between brain and behavior that is consistent with a shift from forced to unforced behavior change. Here we propose how an overlooked aspect of reinforcement learning can be leveraged using a simple yet critical feature of experience that is not reliant on willpower: Bringing awareness to one’s subjective experience and behavior can produce a change in valuation of learned but unhealthy behaviors, leading to self-regulatory shifts that result in sustainable behavior change without force.

Unpacking within- and between-person effects of unstructured socializing and differential association on solo- and co-offending

Unstructured socializing and differential association are two key explanations of peer influence. Unstructured socializing serves as a situational context that promotes antisocial behavior, whereas differential association with delinquent peers leads to learned behavior. Building on these perspectives and prior research, the present study models persons as contexts and examines the impact of unstructured socializing and peer delinquency on solo- and co-offending. Specifically, we use generalized linear mixed models to separate within, between, and person-context effects on offending alone and with peers, and test for interaction effects. Key findings include significant within-individual and between-individual effects of unstructured socializing and peer delinquency on co-offending, significant person-context effects of peer delinquency on co-offending, and significant within, between, and person-context effects of peer delinquency on solo-offending. Among comparable significant relationships, peer delinquency effects were notably stronger than unstructured socializing effects. Finally, interaction models revealed that within-individual effects of unstructured socializing and peer delinquency were attenuated among those with high average peer delinquency over time. The findings hold important implications for future empirical tests of theories of peer influence and for policies and programs aimed at controlling peer influence processes on offending alone and with peers.

Packet-Based Intrusion Detection Using Bayesian Topic Models in Mobile Edge Computing

In this paper, a network intrusion detection system is proposed using Bayesian topic model latent Dirichlet allocation (LDA) for mobile edge computing (MEC). The method employs tcpdump packets and extracts multiple features from the packet headers. The tcpdump packets are transferred into documents based on the features. A topic model is trained using only attack-free traffic in order to learn the behavior patterns of normal traffic. Then, the test traffic is analyzed against the learned behavior patterns to measure the extent to which the test traffic resembles the normal traffic. A threshold is defined in the training phase as the minimum likelihood of a host. In the test phase, when a host’s test traffic has a likelihood lower than the host’s threshold, the traffic is labeled as an intrusion. The intrusion detection system is validated using DARPA 1999 dataset. Experiment shows that our method is suitable to protect the security of MEC.

Transient and Persistent Representations of Odor Value in Prefrontal Cortex

The representation of odor in olfactory cortex (piriform) is distributive and unstructured and can only be afforded behavioral significance upon learning. We performed 2-photon imaging to examine the representation of odors in piriform and in two downstream areas, the orbitofrontal cortex (OFC) and the medial prefrontal cortex (mPFC), as mice learned olfactory associations. In piriform, we observed that odor responses were largely unchanged during learning. In OFC, 30% of the neurons acquired robust responses to conditioned stimuli (CS+) after learning, and these responses were gated by internal state and task context. Moreover, direct projections from piriform to OFC can be entrained to elicit learned olfactory behavior. CS+ responses in OFC diminished with continued training, whereas persistent representations of both CS+ and CS- odors emerged in mPFC. Optogenetic silencing indicates that these two brain structures function sequentially to consolidate the learning of appetitive associations.

The Penn Vet Working Dog Center Fit to Work Program: A Formalized Method for Assessing and Developing Foundational Canine Physical Fitness.

Fit to Work is a formalized working dog foundational physical fitness assessment and development program. The Penn Vet Working Dog Center developed this program to address the needs of working dog handlers, trainers, and programs for simple, effective, and efficient methods to develop and assess working dog physical fitness. Fit to Work focuses on the foundational fitness modalities of strength, stability, mobility, and proprioception. The Penn Vet Working Dog Center piloted and refined this program over 3 months in a closed population of 31 working dogs in training. Fit to Work consists of posture development and maintenance, warm-up and cool-down routines, training exercises, and assessment methods. To simplify implementation for dogs and personnel, the foundational training program incorporates a discrete number of exercises, standardized progression steps, defined criteria for progression, and a reduced emphasis on learned behaviors. Fit to Work also enables safe and progressive assessment of foundational fitness through a tiered and inexpensive process. Future research will focus on validation of training and assessment methods, development of assessment standards, and correlation of physical fitness with operational performance.

Automated and rapid self-report of nociception in transgenic mice

There are currently no rapid, operant pain behaviors in rodents that use a self-report to directly engage higher-order brain circuitry. We have developed a pain detection assay consisting of a lick behavior in response to optogenetic activation of predominantly nociceptive peripheral afferent nerve fibers in head-restrained transgenic mice expressing ChR2 in TRPV1 containing neurons. TRPV1-ChR2-EYFP mice (n = 5) were trained to provide lick reports to the detection of light-evoked nociceptive stimulation to the hind paw. Using simultaneous video recording, we demonstrate that the learned lick behavior may prove more pertinent in investigating brain driven pain processes than the reflex behavior. Within sessions, the response bias of transgenic mice changed with respect to lick behavior but not reflex behavior. Furthermore, response similarity between the lick and reflex behaviors diverged near perceptual threshold. Our nociceptive lick-report detection assay will enable a host of investigations into the millisecond, single cell, neural dynamics underlying pain processing in the central nervous system of awake behaving animals.

Experience selectively alters functional connectivity within a neural network to predict learned behavior in juvenile songbirds

One of the central questions of neuroethology is how specialized brain areas communicate to form dynamic networks that support complex cognitive and behavioral processes. Developmental song learning in the male zebra finch songbird (Taeniopygia guttata) provides a unique window into the complex interplay among sensory, sensorimotor, and motor network nodes. The foundation of a young male's song structure is the sensory memory he forms during interactions with an adult "tutor." However, even in the absence of tutoring, juveniles produce a song-like behavior. Thus, by controlling a juvenile male's tutor exposure, we can examine how tutor experience affects distributed neural networks and how network properties predict behavior. Here, we used longitudinal, resting-state fMRI (rs-fMRI) functional connectivity (FC) and song analyses to examine known nodes of the song network, and to allow discovery of additional areas functionally related to song learning. We present three major novel findings. First, tutor deprivation significantly reduced the global FC strength of the caudomedial nidopallium (NCM) subregion of the auditory forebrain required for sensory song learning. Second, tutor deprivation resulted in reduced FC between NCM and cerebellar lobule VI, a region analogous to areas that regulate limbic, social, and language functions in humans. Third, NCM FC strength predicted song stereotypy and mediated the relationship between tutoring and stereotypy, thus completing the link between experience, neural network properties, and complex learned behavior.

Why Have Two When One Will Do? Comparing Task Representations across Amygdala and Prefrontal Cortex in Single Neurons and Neuronal Populations

Many brain areas represent aspects of learned behavior. How do representations differ between regions? In this issue of Neuron, Kyriazi etal. (2020) show how the amygdala and prefrontal cortex use distinct strategies to code features of a complex task.

Environmental drivers of movement in a threatened seabird: insights from a mechanistic model and implications for conservation

AbstractAimDetermining the drivers of movement of different life‐history stages is crucial for understanding age‐related changes in survival rates and, for marine top predators, the link between fisheries overlap and incidental mortality (bycatch), which is driving population declines in many taxa. Here, we combine individual tracking data and a movement model to investigate the environmental drivers and conservation implications of divergent movement patterns in juveniles (fledglings) and adults of a threatened seabird, the white‐chinned petrel (Procellaria aequinoctialis).LocationSouth‐west Atlantic Ocean.MethodsWe compare the spatial distributions and movement characteristics of juvenile, breeding and non‐breeding adult petrels, and apply a mechanistic movement model to investigate the extent to which chlorophyll a concentrations (a proxy for food resources) and ocean surface winds drive their divergent distribution patterns. We also consider the conservation implications by determining the relative overlap of each life‐history stage with fishing intensity and reported fishing effort (proxies for bycatch risk).ResultsNaïve individuals fledged with similar flight capabilities (based on distances travelled, flight speeds and track sinuosity) to adults but differed in their trajectories. Comparison of simulations from the mechanistic model with real tracks showed that juvenile movements are best predicted by prevailing wind patterns, whereas adults are attracted to food resources on the Patagonian Shelf. The juveniles initially dispersed to less productive oceanic waters than those used by adults, and overlapped less with fishing activity; however, as they moved westwards towards South America, bycatch risk increased substantially.Main conclusionsThe use of a mechanistic framework provided insights into the ontogeny of movement strategies within the context of learned versus innate behaviour and demonstrated that divergent movement patterns of adults and juveniles can have important implications for the conservation of threatened seabirds.

Legal Transitions without Legitimate Expectations*

Legal Transitions without Legitimate Expectations*

Conservation practices and the formation of vocal dialects in the endangered Puerto Rican parrot, Amazona vittata

Captive breeding is a conservation strategy that often results in behavioural changes in animals born and reared in captivity. Culturally transmitted behaviours, such as learned vocal signals, are particularly prone to the effects of captive breeding because captive animals have limited opportunities to learn these behaviours from wild animals. Changes in learned behaviour could affect the success of reintroduction programmes once captive animals are released into the wild. We tested for vocal divergence of learned calls in Puerto Rican parrots, Amazona vittata. We recorded parrots from two captive populations and two wild populations, representing all extant populations of this species. We also recorded parrots that had been translocated between populations and evaluated changes in their vocal signals over time. Fine-scale acoustic analysis revealed vocal divergence in all four populations. The geographical variation in vocal signals evolved over a time span of 10–40 years, demonstrating that cultural traits can evolve rapidly in managed parrot populations. Parrots that were translocated between populations adopted the new vocal signals. Vocal divergence in this species likely resulted from a combination of historical rearing practices, cultural drift and geographical separation. Managers should consider strategies to facilitate the acquisition of foreign vocal signals prior to release.

THE VALUES OF LEARNING IN THE DANGEROUS MINDS MOVIE BY JOHN N SMITH

The research was conducted to know: how are the educational values on the learning process contained in the film Dangerous Minds. The use of research methods that are seen from the type of research that uses a qualitative study/approach is to observe and direct the film. As for analyzing the authors using a qualitative descriptive analysis technique, that describes the values contained in the film. The results of this research show that there are learning values in Film Dangerous Minds, which are various theories of learning namely, theories of learning behaviorism, learning Theory of cognitivism, learning theory of constructivism, learning theory of humanism. Then several methods of learning are methods of learning questions and answers, methods of learning recitation (giving assignments), methods of learning lectures, learning methods of discussion.

NMDAR-mediated modulation of gap junction circuit regulates olfactory learning in C. elegans

Modulation of gap junction-mediated electrical synapses is a common form of neural plasticity. However, the behavioral consequence of the modulation and the underlying molecular cellular mechanisms are not understood. Here, using a C. elegans circuit of interneurons that are connected by gap junctions, we show that modulation of the gap junctions facilitates olfactory learning. Learning experience weakens the gap junctions and induces a repulsive sensory response to the training odorants, which together decouple the responses of the interneurons to the training odorants to generate learned olfactory behavior. The weakening of the gap junctions results from downregulation of the abundance of a gap junction molecule, which is regulated by cell-autonomous function of the worm homologs of a NMDAR subunit and CaMKII. Thus, our findings identify the function of a gap junction modulation in an in vivo model of learning and a conserved regulatory pathway underlying the modulation.

IMPLEMENTATION OF BEHAVIORISM LEARNING THEORIES IN ARABIC LEARNING PLANNING

<p>The purpose of this research to know the theory of learning behaviorism through BF Skinner's thinking in planning Arabic learning. This research method is literature study with qualitative approach, data is extracted through literature study and analyzed through content analysis. The primary data source in this study is The Theories of Learning by Ratna Willis Dahar. While secondary data in this study were obtained from literature exploration related to the discussion. The results of the analysis show that the BF Skinner theory can be applied in Arabic learning planning that is the material being studied is analyzed up to the units organically, the subject matter is used a module system, learning evaluation must be notified to students, if incorrectly corrected and if properly strengthened, more tests emphasized for the sake of diagnostics, in education prioritizing changing the environment to avoid violations so as not to punish, prioritizing the needs that will lead to operant behavior, the behavior desired by educators are rewarded, the desired behavior is analyzed in small ways, increasingly reaching goals, implementing mastery learning is to learn the material thoroughly according to each time because each child has a different rhythm.</p>

Behavioral changes to repeated takeovers in automated driving: The drivers’ ability to transfer knowledge and the effects of takeover request process

Only a couple of studies evaluated whether drivers of automated vehicles change their takeover behavior when they experience takeover requests repeatedly. Even less evidence was accumulated regarding the question whether drivers are able to transfer learned behavior to takeover situations with varying visibility characteristics and whether drivers’ takeover behavior depends on the takeover process in these situations. This paper therefore examines three research questions. First, it assesses how drivers change their behavior with the repeated experience of a takeover situation with the same visibility (fog or no fog). Second, it tests whether drivers can transfer their learned takeover behavior from a takeover situation with high or low visibility to the same takeover situation with different visibility conditions. Third, it assesses whether drivers’ takeover behavior and their experience of the situation differ between a one-step and a two-step takeover request process. Forty participants experienced a takeover situation three times. Experimental trials varied between-subjects concerning the permanent presence or absence of fog in the adaptation condition, the change of visibility conditions from fog to no fog or vice versa in the transfer condition, and the design of the takeover process with one-step or two-steps. Dependent variables included participants’ takeover time, minimum time-to-collision (TTCmin) with the construction site, deceleration and maximum steering behavior, and their ratings of criticality of the driving situation and perceived effort. Results show that participants adapted their deceleration behavior when repeatedly experiencing a takeover situation with the same visibility characteristics (adaptation condition). Changing these characteristics (transfer condition) lead to increased minimum TTCs, criticality and perceived effort ratings. In general, participants were able to maintain their takeover behavior in takeover situations with varying visibility characteristics indicating that they can transfer their takeover behavior across situations. Finally, the two-step takeover request process was associated with longer takeover times. However, minimum TTCs were larger and maximum steering movements and criticality ratings were lower compared to the one-step process. We conclude that drivers transfer their behavior across takeover situations. However, this performance comes at higher costs in terms of perceived effort and criticality. In addition, two-step takeover request processes should be favored over one-step processes when designing takeover requests. Future studies should examine the validity of the results in various takeover situations and on-the-road studies.

Connectomics Analysis Reveals First-, Second-, and Third-Order Thermosensory and Hygrosensory Neurons in the Adult Drosophila Brain

SummaryAnimals exhibit innate and learned preferences for temperature and humidity—conditions critical for their survival and reproduction. Leveraging a whole-brain electron microscopy volume, we studied the adult Drosophila melanogaster circuitry associated with antennal thermo- and hygrosensory neurons. We have identified two new target glomeruli in the antennal lobe, in addition to the five known ones, and the ventroposterior projection neurons (VP PNs) that relay thermo- and hygrosensory information to higher brain centers, including the mushroom body and lateral horn, seats of learned and innate behavior. We present the first connectome of a thermo- and hygrosensory neuropil, the lateral accessory calyx (lACA), by reconstructing neurons downstream of heating- and cooling-responsive VP PNs. A few mushroom body-intrinsic neurons solely receive thermosensory input from the lACA, while most receive additional olfactory and thermo- and/or hygrosensory PN inputs. Furthermore, several classes of lACA-associated neurons form a local network with outputs to other brain neuropils, suggesting that the lACA serves as a hub for thermo- and hygrosensory circuitry. For example, DN1a neurons link thermosensory PNs in the lACA to the circadian clock via the accessory medulla. Finally, we survey strongly connected downstream partners of VP PNs across the protocerebrum; these include a descending neuron targeted by dry-responsive VP PNs, meaning that just two synapses might separate hygrosensory inputs from motor circuits. These data provide a comprehensive first- and second-order layer analysis of Drosophila thermo- and hygrosensory systems and an initial survey of third-order neurons that could directly modulate behavior.

Characteristics of the Neuronal Support for Operative Behavior Formed by Mono- and Multistep Methods

We report here studies to determine whether, and if so, how, the neuronal support for behavior depends on the number of training steps presented in the history of its formation. A training step is the formation of a new skill consisting of a sequence of behavioral acts whose execution leads to achievement of a result: receipt of food. Rats (Long Evans) were trained to an operant pedal-pressing food-procuring skill using two methods – with one or several stages – and the activity of individual neurons in the retrosplenial dysgranular area of the cortex was recorded. In the group of rats in which the skill was acquired in four steps (multistep), there were significantly more neurons specialized for approach and pedal-pressing (consistently activated during these acts) and the mean firing frequency of neurons with structured but not necessarily consistent activity in the learned behavior was greater; there were also more clusters combining cells with selectively increased activity in the same sets of behavioral acts. In animals trained in a single step, only two neurons specialized for approach and pedal-pressing were seen, though there were more cells with structured activity in behavior, these cells displaying maximum firing frequencies in these acts. Thus, the different number of stages in the history of learning the same operant skill was linked with significant differences in the relative number and pattern of activity of two categories of retrosplenial cortex (RC) neurons: those specialized relative to the acts of the learned behavior and cells with structured but variable activity.

On-Off Adversarially Robust Q-Learning

This letter, presents an “on-off” learning-based scheme to expand the attacker's surface, namely a moving target defense (MTD) framework, while optimally stabilizing an unknown system. We leverage Q-learning to learn optimal strategies with “on-off” actuation to promote unpredictability of the learned behavior against physically plausible attacks. We provide rigorous, theoretical guarantees on the stability of the equilibrium point even when switching. Finally, we develop two adversarial threat models to evaluate the learning agent's ability to generate robust policies based on a distance to uncontrollability.

Malocclusion Classification on 3D Cone-Beam CT Craniofacial Images Using Multi-Channel Deep Learning Models.

Analyzing and interpreting cone-beam computed tomography (CBCT) images is a complicated and often time-consuming process. In this study, we present two different architectures of multi-channel deep learning (DL) models: "Ensemble" and "Synchronized multi-channel", to automatically identify and classify skeletal malocclusions from 3D CBCT craniofacial images. These multi-channel models combine three individual single-channel base models using a voting scheme and a two-step learning process, respectively, to simultaneously extract and learn a visual representation from three different directional views of 2D images generated from a single 3D CBCT image. We also employ a visualization method called "Class-selective Relevance Mapping" (CRM) to explain the learned behavior of our DL models by localizing and highlighting a discriminative area within an input image. Our multi-channel models achieve significantly better performance overall (accuracy exceeding 93%), compared to single-channel DL models that only take one specific directional view of 2D projected image as an input. In addition, CRM visually demonstrates that a DL model based on the sagittal-left view of 2D images outperforms those based on other directional 2D images.Clinical Relevance- the proposed method aims at assisting orthodontist to determine the best treatment path for the patient be it orthodontic or surgical treatment or a combination of both.