Model Of Classical Conditioning Research Articles

CK2 negatively regulates the extinction of remote fear memory

Cognitive behavioral therapy, rooted in exposure therapy, is currently the primary approach employed in the treatment of anxiety-related conditions, including post-traumatic stress disorder (PTSD). In laboratory settings, fear extinction in animals is a commonly employed technique to investigate exposure therapy; however, the precise mechanisms underlying fear extinction remain elusive. Casein kinase 2 (CK2), which regulates neuroplasticity via phosphorylation of its substrates, has a significant influence in various neurological disorders, such as Alzheimer’s disease and Parkinson’s disease, as well as in the process of learning and memory. In this study, we adopted a classical Pavlovian fear conditioning model to investigate the involvement of CK2 in remote fear memory extinction and its underlying mechanisms. The results indicated that the activity of CK2 in the medial prefrontal cortex (mPFC) of mice was significantly upregulated after extinction training of remote cued fear memory. Notably, administration of the CK2 inhibitor CX-4945 prior to extinction training facilitated the extinction of remote fear memory. In addition, CX-4945 significantly upregulated the expression of p-ERK1/2 and p-CREB in the mPFC. Our results suggest that CK2 negatively regulates remote fear memory extinction, at least in part, by inhibiting the ERK-CREB pathway. These findings contribute to our understanding of the underlying mechanisms of remote cued fear extinction, thereby offering a theoretical foundation and identifying potential targets for the intervention and treatment of PTSD.

Synaptic Mechanisms of Delay Eyeblink Classical Conditioning: AMPAR Trafficking and Gene Regulation in an In Vitro Model.

An in vitro model of delay eyeblink classical conditioning was developed to investigate synaptic plasticity mechanisms underlying acquisition of associative learning. This was achieved by replacing real stimuli, such as an airpuff and tone, with patterned stimulation of the cranial nerves using an isolated brainstem preparation from turtle. Here, our primary findings regarding cellular and molecular mechanisms for learning acquisition using this unique approach are reviewed. The neural correlate of the in vitro eyeblink response is a replica of the actual behavior, and features of conditioned responses (CRs) resemble those observed in behavioral studies. Importantly, it was shown that acquisition of CRs did not require the intact cerebellum, but the appropriate timing did. Studies of synaptic mechanisms indicate that conditioning involves two stages of AMPA receptor (AMPAR) trafficking. Initially, GluA1-containing AMPARs are targeted to synapses followed later by replacement by GluA4 subunits that support CR expression. This two-stage process is regulated by specific signal transduction cascades involving PKA and PKC and is guided by distinct protein chaperones. The expression of the brain-derived neurotrophic factor (BDNF) protein is central to AMPAR trafficking and conditioning. BDNF gene expression is regulated by coordinated epigenetic mechanisms involving DNA methylation/demethylation and chromatin modifications that control access of promoters to transcription factors. Finally, a hypothesis is proposed that learning genes like BDNF are poised by dual chromatin features that allow rapid activation or repression in response to environmental stimuli. These in vitro studies have advanced our understanding of the cellular and molecular mechanisms that underlie associative learning.

Direct assessment of overnight parent-child proximity in children with behavioral insomnia: Extending models of operant and classical conditioning

ABSTRACT Introduction Explanatory models of behavioral insomnia typically draw on operant learning theory with behavioral techniques focused on altering parent-child interactions to improve sleep. However, there are no data describing parent-child interactions overnight beyond parent report. In this study we used radio frequency identification technology to quantify parent-child proximity overnight in two groups at elevated risk of behavioral insomnia, Angelman syndrome (AS) and Smith-Magenis syndrome (SMS). Materials and Methods Nineteen children aged 4–15 years (8 with AS, 11 with SMS) participated in a week-long at-home assessment of sleep and overnight parent-child proximity. Sleep parameters were recorded using the Philips Actiwatch 2 and proximity data were recorded using custom-built radio frequency identification watches. Results Three patterns of proximity data between parent-child dyads overnight were evident: “checking” (six with AS, five with SMS), “co-sleeping” (four with SMS) and those who had “no proximity” overnight (two with AS, two with SMS). In the AS group, 25.45% of actigraphy-defined wakes resulted in a parent-child interaction. In the SMS group, 39.34% of wakes resulted in a parent-child interaction. Children who interacted with their parents when settling to sleep were not significantly more likely to interact at waking. Discussion The novel application of radio frequency identification technology is a feasible method for studying overnight parent-child proximity. Profiles of proximity between participants that are not closely aligned with operant models of behavioral insomnia were evident. These results have significant implications for the etiology of poor sleep and the application of behavioral sleep interventions.

Intra-prefrontal cyclosporine potentiates ketamine-induced fear extinction in rats.

Several brain regions, including the medial prefrontal cortex (mPFC), are important in the process of fear extinction learning. Ketamine is a glutamate N-methyl-D-aspartate (NMDA) receptor antagonist, which is shown to play a role in extinction modulation. Ketamine and calcineurin (CN), an intracellular protein phosphatase, have several common targets in the cells. Therefore, in the present study, our aim is to investigate the possible role of calcineurin in the mPFC on the enhancing effects of ketamine in fear extinction. First, different doses of a CN inhibitor, cyclosporine-A (CsA), were micro-injected into the infralimbic (IL) region of the mPFC prior to extinction training in a classical conditioning model in rats. Next, sub-effective doses of CsA (Intra-mPFC) and ketamine (i.p.) were co-administered in another cohort of rats to find their possible interactions. Enzymatic activity of calcineurin was measured in the IL-mPFC following drug administration. We used the elevated plus-maze (EPM) and open field (OF) test for further behavioral assessments. The results showed that CsA can enhance the extinction of conditioned fear and inhibit the enzyme CN at a dose of 20nM. The combination of sub-effective doses of CsA (5nM) and ketamine (10mg/kg) could again enhance the extinction of fear and reduce CN activity in the region. Our results propose that inhibition of CN in the IL-mPFC is involved in the extinction of fear and ketamine enhancement of extinction is probably mediated by reducing CN activity in this part of the brain.

Brain-inspired classical conditioning model.

SummaryClassical conditioning plays a critical role in the learning process of biological brains, and many computational models have been built to reproduce the related classical experiments. However, these models can reproduce and explain only a limited range of typical phenomena in classical conditioning. Based on existing biological findings concerning classical conditioning, we build a brain-inspired classical conditioning (BICC) model. Compared with other computational models, our BICC model can reproduce as many as 15 classical experiments, explaining a broader set of findings than other models have, and offers better computational explainability for both the experimental phenomena and the biological mechanisms of classical conditioning. Finally, we validate our theoretical model on a humanoid robot in three classical conditioning experiments (acquisition, extinction, and reacquisition) and a speed generalization experiment, and the results show that our model is computationally feasible as a foundation for brain-inspired robot classical conditioning.

An Amygdala-Inspired Classical Conditioning Model Implemented on an FPGA for Home Service Robots

This study develops an intelligent system for home service robots mimicking human brain function that can manage common knowledge applicable to any environment and local knowledge reflecting its specific environment. Deep learning is effective for acquiring common knowledge because the performance of deep learning relies on the amounts of training and big training data that can be accessed for such knowledge; however, deep learning is ineffective for acquiring local knowledge because no big training data for such knowledge exist. Thus, we propose a brain-inspired learning model and system for acquiring local knowledge using small training data. We focus on the amygdala because its classical fear conditioning is effective for training using small training data. We propose an amygdala-inspired classical conditioning model comprising multiple self-organizing maps (lateral nucleus) and a fully connected neural network (central nucleus), imitating the function and structure of the amygdala. The proposed model is applied to a task of a waiter robot in a restaurant, and the model can learn customers' preferences after only a few human-robot interactions. We accelerate the computation of the model and reduce its power consumption by proposing a hardware-oriented algorithm for the model and its digital hardware design and implement it in an XCZU9EG field programmable gate array. The hardware-oriented algorithm reduces the multiplication operations and exponential functions requiring huge hardware resources. The performance of the hardware operated at 150 MHz is 1,273 times faster than the software implementation on Arm Cortex-A53, and the power consumption of the chip is 5.009 W.

A flexible and generalizable model of online latent-state learning.

Many models of classical conditioning fail to describe important phenomena, notably the rapid return of fear after extinction. To address this shortfall, evidence converged on the idea that learning agents rely on latent-state inferences, i.e. an ability to index disparate associations from cues to rewards (or penalties) and infer which index (i.e. latent state) is presently active. Our goal was to develop a model of latent-state inferences that uses latent states to predict rewards from cues efficiently and that can describe behavior in a diverse set of experiments. The resulting model combines a Rescorla-Wagner rule, for which updates to associations are proportional to prediction error, with an approximate Bayesian rule, for which beliefs in latent states are proportional to prior beliefs and an approximate likelihood based on current associations. In simulation, we demonstrate the model’s ability to reproduce learning effects both famously explained and not explained by the Rescorla-Wagner model, including rapid return of fear after extinction, the Hall-Pearce effect, partial reinforcement extinction effect, backwards blocking, and memory modification. Lastly, we derive our model as an online algorithm to maximum likelihood estimation, demonstrating it is an efficient approach to outcome prediction. Establishing such a framework is a key step towards quantifying normative and pathological ranges of latent-state inferences in various contexts.

Parylene Based Memristive Devices with Multilevel Resistive Switching for Neuromorphic Applications

In this paper, the resistive switching and neuromorphic behaviour of memristive devices based on parylene, a polymer both low-cost and safe for the human body, is comprehensively studied. The Metal/Parylene/ITO sandwich structures were prepared by means of the standard gas phase surface polymerization method with different top active metal electrodes (Ag, Al, Cu or Ti of ~500 nm thickness). These organic memristive devices exhibit excellent performance: low switching voltage (down to 1 V), large OFF/ON resistance ratio (up to 104), retention (≥104 s) and high multilevel resistance switching (at least 16 stable resistive states in the case of Cu electrodes). We have experimentally shown that parylene-based memristive elements can be trained by a biologically inspired spike-timing-dependent plasticity (STDP) mechanism. The obtained results have been used to implement a simple neuromorphic network model of classical conditioning. The described advantages allow considering parylene-based organic memristors as prospective devices for hardware realization of spiking artificial neuron networks capable of supervised and unsupervised learning and suitable for biomedical applications.

Cognitive Tagging of Neurons: CREMediated Genetic Labeling and Characterization of the Cells Involved in Learning and Memory

In this study, we describe use of Cre-mediated recombination to obtain a permanent genetic labeling of the brain neuronal networks activated during a new experience in animals. This method utilizes bitransgenic Fos-Cre-eGFP mice in which a green fluorescent protein is expressed upon tamoxifen-induced Cre-recombination only in the cells where immediate early gene c-fos expression takes place due to the new experience. We used the classical fear conditioning model to show that ex vivo microscopy of the eGFP protein in Fos-Cre-eGFP mice enables mapping of the neurons of the various brain regions that undergo Cre-recombination during acquisition of a new experience. We exposed the animals to the new environment in brief sessions and demonstrated that double immunohistochemical staining enables a characterization of the types of neocortical and hippocampal neurons that undergo experience-dependent Cre-recombination. Notably, Fos-Cre-eGFP labeled cells appeared to belong to excitatory pyramidal neurons rather than to various types of inhibitory neurons. We also showed that a combination of genetic Cre-eGFP labeling with immunohistochemical staining of the endogenous c-Fos protein allows one to identify and compare the neuronal populations that are activated during two different episodes of new experiences in the same animal. This new approach can be used in a wide spectrum of tasks that require imaging and a comparative analysis of cognitive neuronal networks.

A Rescorla-Wagner drift-diffusion model of conditioning and timing.

Computational models of classical conditioning have made significant contributions to the theoretic understanding of associative learning, yet they still struggle when the temporal aspects of conditioning are taken into account. Interval timing models have contributed a rich variety of time representations and provided accurate predictions for the timing of responses, but they usually have little to say about associative learning. In this article we present a unified model of conditioning and timing that is based on the influential Rescorla-Wagner conditioning model and the more recently developed Timing Drift-Diffusion model. We test the model by simulating 10 experimental phenomena and show that it can provide an adequate account for 8, and a partial account for the other 2. We argue that the model can account for more phenomena in the chosen set than these other similar in scope models: CSC-TD, MS-TD, Learning to Time and Modular Theory. A comparison and analysis of the mechanisms in these models is provided, with a focus on the types of time representation and associative learning rule used.

Fear avoidance model – review of selected reports

SUMMARY: Based on the bio-psycho-social approach, fear-avoidance model can be used in situations when somebody avoids movement because of fear of pain. This model can be applied in groups of patients with low back pain and musculoskeletal pain and explains how acute pain becomes chronic. A simple behavioral model of classical and operant conditioning that explains activity avoidance was developed into a more sophisticated, cognitive-behavioral fear-avoidance model, postulating the existence of a vicious circle that causes increasing disability of patients in chronic pain. The variables involved in this mechanism are catastrophizing, fear of activity, avoiding movement, increased distress and fear-avoidance beliefs. This article also presents some further improvements to the model that include pain intensity and motivational theory. A brief overview of tools used in research on fear-avoidance is also presented. It is recommended to take Fear Avoidance Model in to consideration when working with patients with no improvement and the risk of recurrent episodes of pain. Further studies are needed to empirically verify the fear-avoidance model.

DNA Methylation Adjusts the Specificity of Memories Depending on the Learning Context and Promotes Relearning in Honeybees.

The activity of the epigenetic writers DNA methyltransferases (Dnmts) after olfactory reward conditioning is important for both stimulus-specific long-term memory (LTM) formation and extinction. It, however, remains unknown which components of memory formation Dnmts regulate (e.g., associative vs. non-associative) and in what context (e.g., varying training conditions). Here, we address these aspects in order to clarify the role of Dnmt-mediated DNA methylation in memory formation. We used a pharmacological Dnmt inhibitor and classical appetitive conditioning in the honeybee Apis mellifera, a well characterized model for classical conditioning. We quantified the effect of DNA methylation on naïve odor and sugar responses, and on responses following olfactory reward conditioning. We show that (1) Dnmts do not influence naïve odor or sugar responses, (2) Dnmts do not affect the learning of new stimuli, but (3) Dnmts influence odor-coding, i.e., ‘correct’ (stimulus-specific) LTM formation. Particularly, Dnmts reduce memory specificity when experience is low (one-trial training), and increase memory specificity when experience is high (multiple-trial training), generating an ecologically more useful response to learning. (4) In reversal learning conditions, Dnmts are involved in regulating both excitatory (re-acquisition) and inhibitory (forgetting) processes.

A System Computational Model of Implicit Emotional Learning.

Nowadays, the experimental study of emotional learning is commonly based on classical conditioning paradigms and models, which have been thoroughly investigated in the last century. Unluckily, models based on classical conditioning are unable to explain or predict important psychophysiological phenomena, such as the failure of the extinction of emotional responses in certain circumstances (for instance, those observed in evaluative conditioning, in post-traumatic stress disorders and in panic attacks). In this manuscript, starting from the experimental results available from the literature, a computational model of implicit emotional learning based both on prediction errors computation and on statistical inference is developed. The model quantitatively predicts (a) the occurrence of evaluative conditioning, (b) the dynamics and the resistance-to-extinction of the traumatic emotional responses, (c) the mathematical relation between classical conditioning and unconditioned stimulus revaluation. Moreover, we discuss how the derived computational model can lead to the development of new animal models for resistant-to-extinction emotional reactions and novel methodologies of emotions modulation.

Regulation of BDNF chromatin status and promoter accessibility in a neural correlate of associative learning

Brain-derived neurotrophic factor (BDNF) gene expression critically controls learning and its aberrant regulation is implicated in Alzheimer's disease and a host of neurodevelopmental disorders. The BDNF gene is target of known DNA regulatory mechanisms but details of its activity-dependent regulation are not fully characterized. We performed a comprehensive analysis of the epigenetic regulation of the turtle BDNF gene (tBDNF) during a neural correlate of associative learning using an in vitro model of eye blink classical conditioning. Shortly after conditioning onset, the results from ChIP-qPCR show conditioning-dependent increases in methyl-CpG-binding protein 2 (MeCP2) and repressor basic helix-loop-helix binding protein 2 (BHLHB2) binding to tBDNF promoter II that corresponds with transcriptional repression. In contrast, enhanced binding of ten-eleven translocation protein 1 (Tet1), extracellular signal-regulated kinase 1/2 (ERK1/2), and cAMP response element-binding protein (CREB) to promoter III corresponds with transcriptional activation. These actions are accompanied by rapid modifications in histone methylation and phosphorylation status of RNA polymerase II (RNAP II). Significantly, these remarkably coordinated changes in epigenetic factors for two alternatively regulated tBDNF promoters during conditioning are controlled by Tet1 and ERK1/2. Our findings indicate that Tet1 and ERK1/2 are critical partners that, through complementary functions, control learning-dependent tBDNF promoter accessibility required for rapid transcription and acquisition of classical conditioning.

Eyeblink classical conditioning and post-traumatic stress disorder - a model systems approach.

Not everyone exposed to trauma suffers flashbacks, bad dreams, numbing, fear, anxiety, sleeplessness, hyper-vigilance, hyperarousal, or an inability to cope, but those who do may suffer from post-traumatic stress disorder (PTSD). PTSD is a major physical and mental health problem for military personnel and civilians exposed to trauma. There is still debate about the incidence and prevalence of PTSD especially among the military, but for those who are diagnosed, behavioral therapy and drug treatment strategies have proven to be less than effective. A number of these treatment strategies are based on rodent fear conditioning research and are capable of treating only some of the symptoms because the extinction of fear does not deal with the various forms of hyper-vigilance and hyperarousal experienced by people with PTSD. To help address this problem, we have developed a preclinical eyeblink classical conditioning model of PTSD in which conditioning and hyperarousal can both be extinguished. We review this model and discuss findings showing that unpaired stimulus presentations can be effective in reducing levels of conditioning and hyperarousal even when unconditioned stimulus intensity is reduced to the point where it is barely capable of eliciting a response. These procedures have direct implications for the treatment of PTSD and could be implemented in a virtual reality environment.

Sequential Delivery of Synaptic GluA1- and GluA4-containing AMPA Receptors (AMPARs) by SAP97 Anchored Protein Complexes in Classical Conditioning

Multiple signaling pathways are involved in AMPAR trafficking to synapses during synaptic plasticity and learning. The mechanisms for how these pathways are coordinated in parallel but maintain their functional specificity involves subcellular compartmentalization of kinase function by scaffolding proteins, but how this is accomplished is not well understood. Here, we focused on characterizing the molecular machinery that functions in the sequential synaptic delivery of GluA1- and GluA4-containing AMPARs using an in vitro model of eyeblink classical conditioning. We show that conditioning induces the interaction of selective protein complexes with the key structural protein SAP97, which tightly regulates the synaptic delivery of GluA1 and GluA4 AMPAR subunits. The results demonstrate that in the early stages of conditioning the initial activation of PKA stimulates the formation of a SAP97-AKAP/PKA-GluA1 protein complex leading to synaptic delivery of GluA1-containing AMPARs through a SAP97-PSD95 interaction. This is followed shortly thereafter by generation of a SAP97-KSR1/PKC-GluA4 complex for GluA4 AMPAR subunit delivery again through a SAP97-PSD95 interaction. These data suggest that SAP97 forms the molecular backbone of a protein scaffold critical for delivery of AMPARs to the PSD during conditioning. Together, the findings reveal a cooperative interaction of multiple scaffolding proteins for appropriately timed delivery of subunit-specific AMPARs to synapses and support a sequential two-stage model of AMPAR synaptic delivery during classical conditioning.

Consumers’ Attitude to the Protest Against Lady Gaga’s Concert: An Exploratory Study

Lady gaga is an American singer who has won 5 Grammy Awards. In the middle of 2012, she was requested to have concert in Jakarta with the contract value of tens billion. The concert was protested by a number of groups. The promoter had approached the pressure groups and negotiated the dressing.However, Lady Gaga’s management canceled the concert for security consideration.The objectives of the studyare:(1) to explore consumers’ attitude to the protest for the cancelation of Lady Gaga’s concert; and (2) using classical conditioning and expectancy-value theory, to explain consumers’ attitude to the protest.The study used focus group to collect data. The collected data was then transcribed and analyzed by content analysis.The results show that informants’ opinions can be classified into two groups: agreement and disagreement with the protest for the cancelation of Lady Gaga’s concert. Informants either agree or disagree for some reasons. Classical conditioning theory can explain either consumer’s attitude. The difference is the object of consumers’ attitude who agreed was Lady Gaga herself, while the object of disagreement was the pressure group that sponsored the protest. The attitude of the disagreement can also be explained by expectancy-value theory. DOI : https://doi.org/10.21632/irjbs.6.3.149-169 Keywords: Protest, Classical Conditioning Model, Expectancy-Value Theory, Focus Group, Qualitative Content Analysis

Identification of a Functionally Distinct Truncated BDNF mRNA Splice Variant and Protein in Trachemys scripta elegans

Brain-derived neurotrophic factor (BDNF) has a diverse functional role and complex pattern of gene expression. Alternative splicing of mRNA transcripts leads to further diversity of mRNAs and protein isoforms. Here, we describe the regulation of BDNF mRNA transcripts in an in vitro model of eyeblink classical conditioning and a unique transcript that forms a functionally distinct truncated BDNF protein isoform. Nine different mRNA transcripts from the BDNF gene of the pond turtle Trachemys scripta elegans (tBDNF) are selectively regulated during classical conditioning: exon I mRNA transcripts show no change, exon II transcripts are downregulated, while exon III transcripts are upregulated. One unique transcript that codes from exon II, tBDNF2a, contains a 40 base pair deletion in the protein coding exon that generates a truncated tBDNF protein. The truncated transcript and protein are expressed in the naïve untrained state and are fully repressed during conditioning when full-length mature tBDNF is expressed, thereby having an alternate pattern of expression in conditioning. Truncated BDNF is not restricted to turtles as a truncated mRNA splice variant has been described for the human BDNF gene. Further studies are required to determine the ubiquity of truncated BDNF alternative splice variants across species and the mechanisms of regulation and function of this newly recognized BDNF protein.

A Hypothetical Universal Model of Cerebellar Function: Reconsideration of the Current Dogma

The cerebellum is commonly studied in the context of the classical eyeblink conditioning model, which attributes an adaptive motor function to cerebellar learning processes. This model of cerebellar function has quite a few shortcomings and may in fact be somewhat deficient in explaining the myriad functions attributed to the cerebellum, functions ranging from motor sequencing to emotion and cognition. The involvement of the cerebellum in these motor and non-motor functions has been demonstrated in both animals and humans in electrophysiological, behavioral, tracing, functional neuroimaging, and PET studies, as well as in clinical human case studies. A closer look at the cerebellum's evolutionary origin provides a clue to its underlying purpose as a tool which evolved to aid predation rather than as a tool for protection. Based upon this evidence, an alternative model of cerebellar function is proposed, one which might more comprehensively account both for the cerebellum's involvement in a myriad of motor, affective, and cognitive functions and for the relative simplicity and ubiquitous repetitiveness of its circuitry. This alternative model suggests that the cerebellum has the ability to detect coincidences of events, be they sensory, motor, affective, or cognitive in nature, and, after having learned to associate these, it can then trigger (or "mirror") these events after having temporally adjusted their onset based on positive/negative reinforcement. The model also provides for the cerebellum's direction of the proper and uninterrupted sequence of events resulting from this learning through the inhibition of efferent structures (as demonstrated in our lab).

Blockade of Stimulus Convergence in Amygdala Neurons Disrupts Taste Associative Learning

Humans and non-human animals learn associations of temporally contingent stimuli to better cope with the changing environment. In animal models of classical conditioning, a neutral conditioned stimulus (CS) predicts an aversive unconditioned stimulus (US). Several lines of indirect evidence indicate that this learning may rely on stimulus convergence in a subset of neurons, but this hypothesis has not been directly tested. In the current study, we tested this hypothesis using a pharmacogenetic approach, the cAMP response element-binding protein (CREB)/Allatostatin Receptor system, to target a subset of amygdala neurons receiving convergent stimuli in mice during conditioned taste aversion. Virally infected basolateral amygdala neurons with higher CREB levels were predominantly active during CS presentation. Blocking stimulus convergence in infected neurons by silencing them during US disrupted taste associative memory. Moreover, silencing infected neurons only during CS also disrupted associative memory formation. These results provide support for the notion that convergent inputs of CS and US in a subpopulation of neurons are critical for associative memory formation.